- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianUniformMixture
-
Holds the cutoff value.
- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianUniformMixture.Parameterizer
-
- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LDF
-
Scaling constant, to limit value range to 1/c
- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LDF.Parameterizer
-
Scaling constant, to limit value range to 1/c
- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC
-
Parameter c: damping factor.
- c - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer
-
Parameter c: damping coefficient.
- c - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.FastutilIntOpenHashSetModifiableDBIDs.IntOpenHashSet
-
Scan position for pop().
- c - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization
-
Count the number of values seen.
- c - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.RationalQuadraticKernelFunction
-
Constant term c.
- c - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.RationalQuadraticKernelFunction.Parameterizer
-
C parameter
- c - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.SigmoidKernelFunction
-
Scaling factor c, bias theta
- c - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.SigmoidKernelFunction.Parameterizer
-
C parameter, theta parameter
- c - Variable in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D.Triangle
-
References to points in Delaunay2D.points
- c - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution
-
The constant
- c - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction.SetStyleAction
-
Clustering to use
- c - Variable in class tutorial.clustering.SameSizeKMeansAlgorithm.PreferenceComparator
-
Meta to use for comparison.
- C1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
-
- C1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLMMEstimator
-
Estimation constants
- C2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
-
- C2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLMMEstimator
-
Estimation constants
- C3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
-
- C3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLMMEstimator
-
Estimation constants
- C_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianUniformMixture.Parameterizer
-
Parameter to specify the cutoff.
- C_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LDF.Parameterizer
-
Option ID for c
- C_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer
-
Parameter to specify the c.
- C_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.RationalQuadraticKernelFunction.Parameterizer
-
C parameter
- C_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.SigmoidKernelFunction.Parameterizer
-
C parameter: scaling
- ca - Variable in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D.Triangle
-
References to neighbor triangles
- cache - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.CachedDistanceQuery
-
Cache
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction
-
The distance matrix
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction.Parameterizer
-
The distance matrix
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction
-
The distance cache
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction.Parameterizer
-
The distance matrix
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedSparseDoubleDistanceFunction
-
The distance cache
- cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedSparseFloatDistanceFunction
-
The distance cache
- cache - Variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary
-
Cache
- CACHE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix.Parameterizer
-
Parameter that specifies the name of the directory to be re-parsed.
- CACHE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceKNNLists.Parameterizer
-
Parameter that specifies the name of the directory to be re-parsed.
- CACHE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceRangeQueries.Parameterizer
-
Parameter that specifies the name of the directory to be re-parsed.
- CACHE_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.CachedDoubleDistanceKNNPreprocessor.Factory.Parameterizer
-
Option ID for the kNN file.
- CACHE_SHIFT - Static variable in interface de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.Histogram
-
This parameter controls the cache size used for dynamic histograms before
setting the initial thresholds.
- CACHE_SIZE_ID - Static variable in class de.lmu.ifi.dbs.elki.persistent.LRUCachePageFileFactory.Parameterizer
-
Parameter to specify the size of the cache in bytes, must be an integer
equal to or greater than 0.
- cachec - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram
-
Cache for data to be inserted.
- CachedDistanceQuery(DistanceQuery<V>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.CachedDistanceQuery
-
Constructor.
- CachedDoubleDistanceKNNPreprocessor<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Preprocessor that loads an existing cached kNN result.
- CachedDoubleDistanceKNNPreprocessor(Relation<O>, DistanceFunction<? super O>, int, File) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.CachedDoubleDistanceKNNPreprocessor
-
Constructor.
- CachedDoubleDistanceKNNPreprocessor.Factory<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
The parameterizable factory.
- CachedDoubleDistanceKNNPreprocessor.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Parameterization class.
- CacheDoubleDistanceInOnDiskMatrix<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Precompute an on-disk distance matrix, using double precision.
- CacheDoubleDistanceInOnDiskMatrix(Database, DistanceFunction<? super O>, File) - Constructor for class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix
-
Constructor.
- CacheDoubleDistanceInOnDiskMatrix.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Parameterization class.
- CacheDoubleDistanceKNNLists<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Precompute the k nearest neighbors in a disk cache.
- CacheDoubleDistanceKNNLists(Database, DistanceFunction<? super O>, int, File) - Constructor for class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceKNNLists
-
Constructor.
- CacheDoubleDistanceKNNLists.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Parameterization class.
- CacheDoubleDistanceRangeQueries<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Precompute the k nearest neighbors in a disk cache.
- CacheDoubleDistanceRangeQueries(Database, DistanceFunction<? super O>, double, File) - Constructor for class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceRangeQueries
-
Constructor.
- CacheDoubleDistanceRangeQueries.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Parameterization class.
- cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram
-
Cache fill size
- cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram
-
Cache fill size
- CacheFloatDistanceInOnDiskMatrix<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Precompute an on-disk distance matrix, using float precision.
- CacheFloatDistanceInOnDiskMatrix(Database, DistanceFunction<? super O>, File) - Constructor for class de.lmu.ifi.dbs.elki.application.cache.CacheFloatDistanceInOnDiskMatrix
-
Constructor.
- CacheFloatDistanceInOnDiskMatrix.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.application.cache
-
Parameterization class.
- cacheposs - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram
-
Cache for positions to be inserted.
- cacheSize - Variable in class de.lmu.ifi.dbs.elki.persistent.LRUCache
-
The maximum number of objects in this cache.
- cacheSize - Variable in class de.lmu.ifi.dbs.elki.persistent.LRUCachePageFileFactory
-
Cache size, in bytes.
- cacheSize - Variable in class de.lmu.ifi.dbs.elki.persistent.LRUCachePageFileFactory.Parameterizer
-
Cache size, in bytes.
- cacheSizeBytes - Variable in class de.lmu.ifi.dbs.elki.persistent.LRUCache
-
Cache size in bytes.
- cachev - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram
-
Cache for data to be inserted.
- cachevals - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram
-
Cache for data to be inserted.
- calcP_i(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScaling
-
Compute p_i (Gaussian distribution, outliers)
- calcPosterior(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScaling
-
Compute the a posterior probability for the given parameters.
- calcQ_i(double, double) - Static method in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScaling
-
Compute q_i (Exponential distribution, inliers)
- calcScales(Relation<? extends SpatialComparable>) - Static method in class de.lmu.ifi.dbs.elki.math.scales.Scales
-
Compute a linear scale for each dimension.
- calculate_MDEF_norm(ALOCI.Node, ALOCI.Node) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI
-
Method for the MDEF calculation
- calculateApproximation(DBID, V) - Method in class de.lmu.ifi.dbs.elki.index.vafile.VAFile
-
Calculate the VA file position given the existing borders.
- calculateContrast(Relation<? extends NumberVector>, HiCS.HiCSSubspace, ArrayList<ArrayDBIDs>, Random) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS
-
Calculates the actual contrast of a given subspace.
- calculateDOF(MeanVariance, MeanVariance) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.WelchTTest
-
Calculates the degree of freedom according to Welch-Satterthwaite
- calculateFullApproximation(DBID, V) - Method in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile
-
Calculate the VA file position given the existing borders.
- calculatePartialApproximation(DBID, NumberVector, List<DoubleObjPair<DAFile>>) - Static method in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile
-
Calculate partial vector approximation.
- calculatePValue(double, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.WelchTTest
-
Calculates the two-sided p-Value of the underlying t-Distribution with v
degrees of freedom
- calculateSelectivityCoeffs(List<DoubleObjPair<DAFile>>, NumberVector, double) - Static method in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile
-
Calculate selectivity coefficients.
- calculateSubspaces(Relation<? extends NumberVector>, ArrayList<ArrayDBIDs>, Random) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS
-
Identifies high contrast subspaces in a given full-dimensional database.
- calculateTestStatistic(double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.KolmogorovSmirnovTest
-
Calculates the maximum distance between the two empirical CDFs of two data
samples.
- calculateTestStatistic(MeanVariance, MeanVariance) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.WelchTTest
-
Calculate the statistic of Welch's t test using statistical moments of the
provided data samples
- call() - Method in class de.lmu.ifi.dbs.elki.parallel.ParallelExecutor.BlockArrayRunner
-
- callback - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs.ThumbnailThread.Task
-
Runnable to call back
- camera - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance.Shared
-
Camera handling class
- camera - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.util.Arcball1DOFAdapter
-
The true camera.
- cameraChanged() - Method in interface de.lmu.ifi.dbs.elki.visualization.parallel3d.util.Simple1DOFCamera.CameraListener
-
Camera changed.
- CanberraDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Canberra distance function, a variation of Manhattan distance.
- CanberraDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.CanberraDistanceFunction
-
Constructor.
- CanberraDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Parameterization class.
- canBulkLoad() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Test whether a bulk insert is still possible.
- Cand(double[][], double, int) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.AutotuningPCA.Cand
-
Constructor.
- candidates - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.GeneralizedOPTICS.Instance
-
Current list of candidates.
- candidates - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSList.Instance
-
Current list of candidates.
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.BiweightKernelDensityFunction
-
Canonical bandwidth: 35^(1/5)
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.CosineKernelDensityFunction
-
Canonical bandwidth.
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction
-
Canonical bandwidth: 15^(1/5)
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.GaussianKernelDensityFunction
-
Canonical bandwidth: (1./(4*pi))^(1/10)
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriangularKernelDensityFunction
-
Canonical bandwidth.
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TricubeKernelDensityFunction
-
Canonical bandwidth.
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriweightKernelDensityFunction
-
Canonical bandwidth: (9450/143)^(1/5)
- CANONICAL_BANDWIDTH - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.UniformKernelDensityFunction
-
Canonical bandwidth: (9/2)^(1/5)
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.BiweightKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.CosineKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.GaussianKernelDensityFunction
-
- canonicalBandwidth() - Method in interface de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.KernelDensityFunction
-
Get the canonical bandwidth for this kernel.
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriangularKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TricubeKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriweightKernelDensityFunction
-
- canonicalBandwidth() - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.UniformKernelDensityFunction
-
- canonicalClassName(Class<?>, Package) - Static method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassParameter
-
Get the "simple" form of a class name.
- canonicalClassName(Class<?>, Class<?>) - Static method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassParameter
-
Get the "simple" form of a class name.
- CanopyPreClustering<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Canopy pre-clustering is a simple preprocessing step for clustering.
- CanopyPreClustering(DistanceFunction<? super O>, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.CanopyPreClustering
-
Constructor.
- CanopyPreClustering.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Parameterization class
- canRun() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel
-
Test if this tab is ready-to-run
- canvas - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.OpenGL3DParallelCoordinates.Instance
-
The OpenGL canvas
- CanvasSize - Class in de.lmu.ifi.dbs.elki.visualization.projections
-
Size of a canvas.
- CanvasSize(double, double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.projections.CanvasSize
-
Constructor.
- canVisualize(Relation<?>, AbstractMTree<?, ?, ?, ?>) - Static method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization
-
Test for a visualizable index in the context's database.
- capacity - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree
-
Capacity of a node.
- capacity(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Capacity of the vector v.
- capital_n - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut
-
Set sizes, total and current iteration
- capital_n_star - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut
-
Set sizes, total and current iteration
- cardinality() - Method in class de.lmu.ifi.dbs.elki.data.BitVector
-
Compute the vector cardinality (uncached!)
- cardinality(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Compute the cardinality (number of set bits)
- cardinality(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Compute the cardinality (number of set bits)
Low-endian layout for the array.
- CARRIAGE_RETURN - Static variable in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Carriage return character.
- CASH<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
-
The CASH algorithm is a subspace clustering algorithm based on the Hough
transform.
- CASH(int, int, int, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH
-
Constructor.
- CASH.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
-
Parameterization class.
- CASHInterval - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash
-
Provides a unique interval represented by its id, a hyper bounding box
representing the alpha intervals, an interval of the corresponding distance,
and a set of objects ids associated with this interval.
- CASHInterval() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval
-
Empty constructor for Externalizable interface.
- CASHInterval(double[], double[], CASHIntervalSplit, ModifiableDBIDs, int, int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval
-
Provides a unique interval represented by its id, a hyper bounding box and
a set of objects ids associated with this interval.
- CASHIntervalSplit - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash
-
Supports the splitting of CASH intervals.
- CASHIntervalSplit(Relation<ParameterizationFunction>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHIntervalSplit
-
Initializes the logger and sets the debug status to the given value.
- cast(Object) - Method in class de.lmu.ifi.dbs.elki.data.type.SimpleTypeInformation
-
Cast the object to type T (actually to the given restriction class!).
- CategorialDataAsNumberVectorParser<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
A very simple parser for categorial data, which will then be encoded as
numbers.
- CategorialDataAsNumberVectorParser(NumberVector.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.CategorialDataAsNumberVectorParser
-
Constructor with defaults.
- CategorialDataAsNumberVectorParser(CSVReaderFormat, long[], NumberVector.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.CategorialDataAsNumberVectorParser
-
Constructor.
- CategorialDataAsNumberVectorParser.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Parameterization class.
- CauchyDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Cauchy distribution.
- CauchyDistribution(double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
Constructor with default random.
- CauchyDistribution(double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
Constructor.
- CauchyDistribution(double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
Constructor.
- CauchyDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Parameterization class
- CauchyMADEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Estimate Cauchy distribution parameters using Median and MAD.
- CauchyMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.CauchyMADEstimator
-
Private constructor, use static instance!
- CauchyMADEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Parameterization class.
- CauchyRandomProjectionFamily - Class in de.lmu.ifi.dbs.elki.data.projection.random
-
Random projections using Cauchy distributions (1-stable).
- CauchyRandomProjectionFamily(RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.data.projection.random.CauchyRandomProjectionFamily
-
Constructor.
- CauchyRandomProjectionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.data.projection.random
-
Parameterization class.
- CBLOF<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering
-
Cluster-based local outlier factor (CBLOF).
- CBLOF(NumberVectorDistanceFunction<? super O>, ClusteringAlgorithm<Clustering<MeanModel>>, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF
-
Constructor.
- CBLOF.Parameterizer<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering
-
Parameterization class.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution
-
Static version of the CDF of the beta distribution
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
PDF function, static version.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
- cdf(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
Cumulative density function.
- cdf(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution
-
The CDF, static version.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution
-
- cdf(double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution
-
Return the cumulative density function at the given value.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution
-
The CDF, static version.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
-
- cdf(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
-
Cumulative density, static version
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
-
Cumulative probability density function (CDF) of an exgauss distribution.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
The CDF, static version.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedExtremeValueDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedExtremeValueDistribution
-
CDF of GEV distribution
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticAlternateDistribution
-
Cumulative density function.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticAlternateDistribution
-
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticDistribution
-
Cumulative density function.
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedParetoDistribution
-
CDF of GPD distribution
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedParetoDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GumbelDistribution
-
CDF of Gumbel distribution
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GumbelDistribution
-
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.InverseGaussianDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.InverseGaussianDistribution
-
Cumulative probability density function (CDF) of a Wald distribution.
- cdf(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.KappaDistribution
-
Cumulative density function.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.KappaDistribution
-
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LaplaceDistribution
-
- cdf(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LaplaceDistribution
-
Cumulative density, static version
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogGammaDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogGammaDistribution
-
The CDF, static version.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogisticDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogisticDistribution
-
Cumulative density function.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogLogisticDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogLogisticDistribution
-
Cumulative density function.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogNormalDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogNormalDistribution
-
Cumulative probability density function (CDF) of a normal distribution.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
- cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
Cumulative probability density function (CDF) of a normal distribution.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution
-
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.RayleighDistribution
-
- cdf(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.RayleighDistribution
-
CDF of Rayleigh distribution
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.SkewGeneralizedNormalDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.SkewGeneralizedNormalDistribution
-
Cumulative probability density function (CDF) of a normal distribution.
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.StudentsTDistribution
-
- cdf(double, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.StudentsTDistribution
-
Static version of the CDF of the t-distribution for t > 0
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.UniformDistribution
-
- cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.WeibullDistribution
-
CDF of Weibull distribution
- cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.WeibullDistribution
-
- cdim - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate.COPACModel
-
Correlation dimensionality.
- cdist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansAnnulus.Instance
-
Cluster center distances.
- cdist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansCompare.Instance
-
Cluster center distances.
- cdist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansElkan.Instance
-
Cluster center distances
- cdist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansExponion.Instance
-
Cluster center distances.
- cdiv(double, double, double, double, double[], int) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
-
Complex scalar division, writing into buf[off++]
- cells - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Number of cells per dimension.
- center - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node
-
Center vector
- center - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.SOD.SODModel
-
Center vector
- center - Variable in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE.QuadTree
-
Center of mass (NOT center of bounding box)
- CENTER - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.InstanceLogRankNormalization
-
Average value use for NaNs
- centerKernelMatrix(KernelMatrix) - Static method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix
-
Centers the Kernel Matrix in Feature Space according to Smola et.
- centerMatrix(double[][]) - Static method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.KernelMatrix
-
Centers the matrix in feature space according to Smola et Schoelkopf,
Learning with Kernels p. 431 Alters the input matrix.
- CenterOfMassMetaClustering<C extends Clustering<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain
-
Center-of-mass meta clustering reduces uncertain objects to their center of
mass, then runs a vector-oriented clustering algorithm on this data set.
- CenterOfMassMetaClustering(ClusteringAlgorithm<C>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.CenterOfMassMetaClustering
-
Constructor, quite trivial.
- CenterOfMassMetaClustering.Parameterizer<C extends Clustering<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain
-
Parameterization class.
- centers - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain.AssignLabelsByDistance
-
Cluster centers.
- centroid - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.ORCLUSCluster
-
The centroid of this cluster.
- centroid(int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.ClusteringFeature
-
Centroid value in dimension i.
- centroid - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.PROCLUSCluster
-
The centroids of this cluster along each dimension.
- centroid - Variable in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
-
The centroid if the objects belonging to the hyperplane induced by the
correlation.
- centroid(SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
-
Returns the centroid of this SpatialComparable.
- Centroid - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
-
Class to compute the centroid of some data.
- Centroid(int) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.Centroid
-
Constructor.
- CentroidEuclideanDistance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Centroid Euclidean distance.
- CentroidEuclideanDistance() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CentroidEuclideanDistance
-
- CentroidEuclideanDistance.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Parameterization class.
- CentroidLinkage - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage
-
Centroid linkage — Unweighted Pair-Group Method using Centroids
(UPGMC).
- CentroidLinkage() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.CentroidLinkage
-
- CentroidLinkage.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage
-
Class parameterizer.
- CentroidManhattanDistance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Centroid Manhattan Distance
Reference:
Data Clustering for Very Large Datasets Plus Applications
T.
- CentroidManhattanDistance() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CentroidManhattanDistance
-
- CentroidManhattanDistance.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Parameterization class.
- centroids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor
-
Updated cluster centroids
- centroids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor.Instance
-
Updated cluster centroids
- centroids(Relation<? extends NumberVector>, List<? extends Cluster<?>>, NumberVector[], NoiseHandling) - Static method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette
-
Compute centroids.
- CertaintyFactor - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest
-
Certainty factor (CF; Loevinger) interestingness measure.
\( \tfrac{\text{confidence}(X \rightarrow Y) -
\text{support}(Y)}{\text{support}(\neg Y)} \).
- CertaintyFactor() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest.CertaintyFactor
-
Constructor.
- cffactory - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.BIRCHLeafClustering
-
CFTree factory.
- cffactory - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.BIRCHLeafClustering.Parameterizer
-
CFTree factory.
- CFTree - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Partial implementation of the CFTree as used by BIRCH.
- CFTree(BIRCHDistance, BIRCHAbsorptionCriterion, double, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree
-
Constructor.
- CFTree.Factory - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
CF-Tree Factory.
- CFTree.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Parameterization class for CFTrees.
- CFTree.LeafIterator - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Iterator over leaf nodes.
- CFTree.TreeNode - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Inner node.
- chain - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization
-
Keep the list of parameterizations.
- ChainedParameterization - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization
-
Class that allows chaining multiple parameterizations.
- ChainedParameterization(Parameterization...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization
-
Constructor that takes a number of Parameterizations to chain.
- changed - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor
-
Whether the assignment changed during the last iteration.
- changed() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor
-
Get the "has changed" value.
- changed - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor.Instance
-
Changed flag.
- ChangePoint - Class in de.lmu.ifi.dbs.elki.algorithm.timeseries
-
Single Change Point
- ChangePoint(DBIDRef, int, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.timeseries.ChangePoint
-
Constructor.
- ChangePoints - Class in de.lmu.ifi.dbs.elki.algorithm.timeseries
-
Change point detection result Used by change or trend detection algorithms
TODO: we need access to the data labels / timestamp information!
- ChangePoints(String, String) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.timeseries.ChangePoints
-
Result constructor.
- changepoints - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.ChangePoints
-
Change points.
- CHAR_ADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.QuickSelect
-
Adapter for char arrays.
- charset - Variable in class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil.StringSerializer
-
Character set to use.
- charsSinceNewline - Variable in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Flag to signal if we have had a newline recently.
- checkAliases(Class<?>, String, String[]) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckELKIServices
-
Check if aliases are listed completely.
- checkAspectRatio - Variable in class de.lmu.ifi.dbs.elki.visualization.savedialog.SaveOptionsPanel
-
- checkCandidate(double[]) - Method in class de.lmu.ifi.dbs.elki.math.geometry.FilteredConvexHull2D
-
- checkCandidateUpdate(double[]) - Method in class de.lmu.ifi.dbs.elki.math.geometry.FilteredConvexHull2D
-
Check whether a point is inside the current bounds, and update the bounds
- checkClusters(Relation<V>, Object2ObjectMap<long[], List<ArrayModifiableDBIDs>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH
-
Removes the clusters with size < minpts from the cluster map and adds them
to their parents.
- checkConvergence(Collection<AggarwalYuEvolutionary.Individuum>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch
-
check the termination criterion.
- checkCoverTree(CoverTree.Node, int[], int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree
-
Collect some statistics on the tree.
- checkCoverTree(SimplifiedCoverTree.Node, int[], int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree
-
Collect some statistics on the tree.
- checkCSSStatement(String, String) - Static method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Validate a single CSS statement.
- checkCSSStatements(Collection<Pair<String, String>>) - Static method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Validate a set of CSS statements.
- checkDefaultConstructor(Class<?>, CheckParameterizables.State) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
Check for a default constructor.
- checkDependencies() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel
-
Test if the dependencies are still valid.
- checkDependencies() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel
-
Test if the dependencies are still valid.
- checkDependencies() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel
-
Test if the dependencies are still valid.
- checkDimensions(CLIQUEUnit, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Check that the first e dimensions agree.
- checkDistanceFunction(SpatialPrimitiveDistanceFunction<? super O>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
Throws an IllegalArgumentException if the specified distance function is
not an instance of the distance function used by this index.
- checked - Variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGCheckbox
-
Status flag
- CheckELKIServices - Class in de.lmu.ifi.dbs.elki.application.internal
-
Helper application to test the ELKI properties file for "missing"
implementations.
- CheckELKIServices() - Constructor for class de.lmu.ifi.dbs.elki.application.internal.CheckELKIServices
-
- checkForNaNs(NumberVector) - Method in class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores
-
Check for NaN values.
- checkGridCellSizes(int, long) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Perform some sanity checks on the grid cells.
- checkHeap() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap
-
Test whether the heap is still valid.
- checkLower(Subspace, List<Subspace>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU
-
Perform Apriori-style pruning.
- checkName(String) - Static method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Verify that the name is an admissible CSS class name.
- CheckParameterizables - Class in de.lmu.ifi.dbs.elki.application.internal
-
Perform some consistency checks on classes that cannot be specified as Java
interface.
- CheckParameterizables() - Constructor for class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
- checkParameterizables() - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
Validate all "Parameterizable" objects for parts of the API contract that
cannot be specified in Java interfaces (such as constructors, static
methods)
- CheckParameterizables.State - Enum in de.lmu.ifi.dbs.elki.application.internal
-
Current verification state.
- checkParameterizer(Class<?>, Class<? extends AbstractParameterizer>) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
- checkRange(DBIDRange) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.DBIDRangeDistanceFunction
-
Validate the range of DBIDs to use.
- checkRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction
-
- checkRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction
-
- checkRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedSparseDoubleDistanceFunction
-
- checkRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedSparseFloatDistanceFunction
-
- checkSamples(UncertainObject, UncertainObject) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Instance
-
- checkSelected(int[], double[], double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance
-
- checkService(String, String) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckELKIServices
-
Check a single service class
- checkServices(String) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckELKIServices
-
Retrieve all properties and check them.
- checkSupertypes(Class<?>) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
Check all supertypes of a class.
- checkV3Parameterization(Class<?>, CheckParameterizables.State) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
-
Check for a V3 constructor.
- ChengAndChurch<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering
-
Cheng and Church biclustering.
- ChengAndChurch(double, double, int, Distribution) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch
-
Constructor.
- ChengAndChurch.BiclusterCandidate - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering
-
Bicluster candidate.
- ChengAndChurch.CellVisitor - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering
-
Visitor pattern for processing cells.
- ChengAndChurch.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering
-
Parameterization class.
- ChiDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic
-
χ distance function, symmetric version.
- ChiDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiDistanceFunction
-
- ChiDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic
-
Parameterization class, using the static instance.
- ChiDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Chi distribution.
- ChiDistribution(double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
Constructor.
- ChiDistribution(double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
Constructor.
- ChiDistribution(double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
Constructor.
- ChiDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Parameterization class
- child - Variable in class de.lmu.ifi.dbs.elki.gui.configurator.ClassListParameterConfigurator
-
Configurator for children
- child - Variable in class de.lmu.ifi.dbs.elki.gui.configurator.ClassParameterConfigurator
-
Configuration panel for child.
- child - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeAppendChild
-
The child to be appended.
- childconfig - Variable in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
-
Keep a map of parameter
- childiter - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrDesc
-
Iterator over children
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree.TreeNode
-
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster
-
(Finished) child clusters
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster
-
(Finished) child clusters
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode
-
Children.
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node
-
Child nodes, may be null
- children - Variable in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE.QuadTree
-
Child nodes.
- children - Variable in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
-
Child options
- children(IndexTreePath<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode
-
- children - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree.Node
-
Child nodes.
- children - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree.Node
-
Child nodes.
- children(IndexTreePath<E>) - Method in interface de.lmu.ifi.dbs.elki.index.tree.Node
-
Returns an enumeration of the children paths of this node.
- children - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec
-
Children.
- children - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.TrackParameters
-
Tree information: child links
- children - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.AbstractLayout3DPC.AbstractNode
-
Children
- childrenTotal - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster
-
Number of objects in children.
- chisq - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod
-
Chi-Squared information for parameters
- chisq - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
Chi squared distribution (for random generation)
- ChiSquaredDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic
-
χ² distance function, symmetric version.
- ChiSquaredDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiSquaredDistanceFunction
-
- ChiSquaredDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic
-
Parameterization class, using the static instance.
- ChiSquaredDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Chi-Squared distribution (a specialization of the Gamma distribution).
- ChiSquaredDistribution(double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution
-
Constructor.
- ChiSquaredDistribution(double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution
-
Constructor.
- ChiSquaredDistribution(double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution
-
Constructor.
- ChiSquaredDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Parameterization class
- chisquaredProbitApproximation(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
Approximate probit for chi squared distribution
Based on first half of algorithm AS 91
Reference:
D.
- chiSquaredUniformTest(SetDBIDs[], long[], int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C
-
Performs a ChiSquared test to determine whether an attribute has a uniform
distribution.
- chol - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel
-
Decomposition of covariance matrix.
- chol - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.TextbookMultivariateGaussianModel
-
Decomposition of covariance matrix.
- chol - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.TwoPassMultivariateGaussianModel
-
Decomposition of covariance matrix.
- CholeskyDecomposition - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
-
Cholesky Decomposition.
- CholeskyDecomposition(double[][]) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.CholeskyDecomposition
-
Cholesky algorithm for symmetric and positive definite matrix.
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy
-
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy
-
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in interface de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.InsertionStrategy
-
Choose insertion rectangle.
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.LeastEnlargementInsertionStrategy
-
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.LeastEnlargementWithAreaInsertionStrategy
-
- choose(A, ArrayAdapter<? extends SpatialComparable, A>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.LeastOverlapInsertionStrategy
-
- chooseBulkSplitPoint(int, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk.AbstractBulkSplit
-
Computes and returns the best split point.
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestPointsInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestSumPointsInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FirstKInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansInitialization
-
Choose initial means
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansPlusPlusInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.LABInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.OstrovskyInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PAMInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.ParkInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PredefinedInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomlyChosenInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomNormalGeneratedInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomUniformGeneratedInitialMeans
-
- chooseInitialMeans(Database, Relation<? extends NumberVector>, int, NumberVectorDistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.SampleKMeansInitialization
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestPointsInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestSumPointsInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FirstKInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansPlusPlusInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super V>) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMedoidsInitialization
-
Choose initial means
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.LABInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PAMInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.ParkInitialMeans
-
- chooseInitialMedoids(int, DBIDs, DistanceQuery<? super O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomlyChosenInitialMeans
-
- chooseMaximalExtendedSplitAxis(List<? extends SpatialComparable>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk.MaxExtensionBulkSplit
-
Computes and returns the best split axis.
- choosePath(AbstractMTree<?, N, E, ?>, E) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert.MinimumEnlargementInsert
-
- choosePath(AbstractMTree<?, N, E, ?>, E, IndexTreePath<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert.MinimumEnlargementInsert
-
Chooses the best path of the specified subtree for insertion of the given
object.
- choosePath(AbstractMTree<?, N, E, ?>, E) - Method in interface de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert.MTreeInsert
-
Choose the subpath to insert into.
- choosePath(IndexTreePath<E>, SpatialComparable, int, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Chooses the best path of the specified subtree for insertion of the given
mbr at the specified level.
- choosePrime(Random) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
Choose a random prime.
- chooseRemaining(Relation<? extends NumberVector>, DBIDs, DistanceQuery<NumberVector>, int, List<NumberVector>, WritableDoubleDataStore, double, Random) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansPlusPlusInitialMeans
-
Choose remaining means, weighted by distance.
- chooseRemaining(DBIDs, DistanceQuery<?>, int, ArrayModifiableDBIDs, WritableDoubleDataStore, double, Random) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansPlusPlusInitialMeans
-
Choose remaining means, weighted by distance.
- chooseSplitAxis(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split
-
Chooses a split axis.
- chooseSplitPoint(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split
-
Chooses a split axis.
- CircleMarkers - Class in de.lmu.ifi.dbs.elki.visualization.style.marker
-
Simple marker library that just draws colored circles at the given
coordinates.
- CircleMarkers(StyleLibrary) - Constructor for class de.lmu.ifi.dbs.elki.visualization.style.marker.CircleMarkers
-
Constructor
- CircleSegmentsVisualizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments
-
Visualizer to draw circle segments of clusterings and enable interactive
selection of segments.
- CircleSegmentsVisualizer() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer
-
Constructor
- CircleSegmentsVisualizer.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments
-
Instance
- CircleSegmentsVisualizer.Instance.SegmentListenerProxy - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments
-
Proxy element to connect signals.
- CKMeans - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain
-
Run k-means on the centers of each uncertain object.
- CKMeans(KMeans<?, KMeansModel>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.CKMeans
-
Constructor that uses an arbitrary k-means algorithm.
- CKMeans(NumberVectorDistanceFunction<? super NumberVector>, int, int, KMeansInitialization) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.CKMeans
-
Constructor that uses Lloyd's k-means algorithm.
- CKMeans.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain
-
Parameterization class, based on k-means.
- clamp(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
-
Clamp values to a given minimum and maximum.
- CLARA<V> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
Clustering Large Applications (CLARA) is a clustering method for large data
sets based on PAM, partitioning around medoids (
KMedoidsPAM) based on
sampling.
- CLARA(DistanceFunction<? super V>, int, int, KMedoidsInitialization<V>, int, double, boolean, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA
-
Constructor.
- CLARA.CachedDistanceQuery<V> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
Cached distance query.
- CLARA.Parameterizer<V> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
Parameterization class.
- CLARANS<V> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
CLARANS: a method for clustering objects for spatial data mining
is inspired by PAM (partitioning around medoids,
KMedoidsPAM)
and CLARA and also based on sampling.
- CLARANS(DistanceFunction<? super V>, int, int, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS
-
Constructor.
- CLARANS.Assignment - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
Assignment state.
- CLARANS.Parameterizer<V> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans
-
Parameterization class.
- ClarkDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Clark distance function for vector spaces.
- ClarkDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.ClarkDistanceFunction
-
- ClarkDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Parameterization class.
- CLARKE1858_FLATTENING - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1858SpheroidEarthModel
-
Flattening f of the CLARKE1858 Ellipsoid.
- CLARKE1858_INV_FLATTENING - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1858SpheroidEarthModel
-
Inverse flattening 1/f of the CLARKE1858 Ellipsoid.
- CLARKE1858_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1858SpheroidEarthModel
-
Radius of the CLARKE1858 Ellipsoid in m (a).
- Clarke1858SpheroidEarthModel - Class in de.lmu.ifi.dbs.elki.math.geodesy
-
The Clarke 1858 spheroid earth model.
- Clarke1858SpheroidEarthModel() - Constructor for class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1858SpheroidEarthModel
-
Constructor.
- Clarke1858SpheroidEarthModel.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.geodesy
-
Parameterization class.
- CLARKE1880_FLATTENING - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1880SpheroidEarthModel
-
Flattening f of the CLARKE1880 Ellipsoid.
- CLARKE1880_INV_FLATTENING - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1880SpheroidEarthModel
-
Inverse flattening 1/f of the CLARKE1880 Ellipsoid.
- CLARKE1880_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1880SpheroidEarthModel
-
Radius of the CLARKE1880 Ellipsoid in m (a).
- Clarke1880SpheroidEarthModel - Class in de.lmu.ifi.dbs.elki.math.geodesy
-
The Clarke 1880 spheroid earth model.
- Clarke1880SpheroidEarthModel() - Constructor for class de.lmu.ifi.dbs.elki.math.geodesy.Clarke1880SpheroidEarthModel
-
Constructor.
- Clarke1880SpheroidEarthModel.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.geodesy
-
Parameterization class.
- CLASS_EXT - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator
-
- CLASS_EXT_LENGTH - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator
-
- CLASS_LABEL_CLASS_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter.Parameterizer
-
Parameter to specify the class of occurring class labels.
- CLASS_LABEL_INDEX_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter.Parameterizer
-
Optional parameter that specifies the index of the label to be used as
class label, must be an integer equal to or greater than 0.
- ClassGenericsUtil - Class in de.lmu.ifi.dbs.elki.utilities
-
Utilities for handling class instantiation, especially with respect to Java
generics.
- ClassGenericsUtil() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
-
Fake Constructor.
- ClassicMultidimensionalScalingTransform<I,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Rescale the data set using multidimensional scaling, MDS.
- ClassicMultidimensionalScalingTransform(int, PrimitiveDistanceFunction<? super I>, NumberVector.Factory<O>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform
-
Constructor.
- ClassicMultidimensionalScalingTransform.Parameterizer<I,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Parameterization class.
- Classifier<O> - Interface in de.lmu.ifi.dbs.elki.algorithm.classification
-
A Classifier is to hold a model that is built based on a database, and to
classify a new instance of the same type.
- ClassifierHoldoutEvaluationTask<O> - Class in de.lmu.ifi.dbs.elki.application
-
Evaluate a classifier.
- ClassifierHoldoutEvaluationTask(DatabaseConnection, Collection<IndexFactory<?>>, Classifier<O>, Holdout) - Constructor for class de.lmu.ifi.dbs.elki.application.ClassifierHoldoutEvaluationTask
-
Constructor.
- ClassifierHoldoutEvaluationTask.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.application
-
Parameterization class.
- classify(O) - Method in interface de.lmu.ifi.dbs.elki.algorithm.classification.Classifier
-
Classify a single instance.
- classify(O) - Method in class de.lmu.ifi.dbs.elki.algorithm.classification.KNNClassifier
-
- classify(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.classification.PriorProbabilityClassifier
-
- ClassInstantiationException - Exception in de.lmu.ifi.dbs.elki.utilities.exceptions
-
Error thrown when a class cannot be instantiated.
- ClassInstantiationException() - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.ClassInstantiationException
-
Constructor.
- ClassInstantiationException(String) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.ClassInstantiationException
-
Constructor.
- ClassInstantiationException(Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.ClassInstantiationException
-
Constructor.
- ClassInstantiationException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.ClassInstantiationException
-
Constructor.
- ClassLabel - Class in de.lmu.ifi.dbs.elki.data
-
A ClassLabel to identify a certain class of objects that is to discern from
other classes by a classifier.
- ClassLabel() - Constructor for class de.lmu.ifi.dbs.elki.data.ClassLabel
-
ClassLabels need an empty constructor for dynamic access.
- CLASSLABEL - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
A class label.
- ClassLabel.Factory<L extends ClassLabel> - Class in de.lmu.ifi.dbs.elki.data
-
Class label factory.
- classLabelFactory - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter
-
The class label class to use.
- classLabelFactory - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter.Parameterizer
-
The class label factory to use.
- ClassLabelFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
-
Class that turns a label column into a class label column.
- ClassLabelFilter(int, ClassLabel.Factory<?>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter
-
Constructor.
- ClassLabelFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
-
Parameterization class.
- ClassLabelFromPatternFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
-
Streaming filter to derive an outlier class label.
- ClassLabelFromPatternFilter(Pattern, String, String) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter
-
Constructor.
- ClassLabelFromPatternFilter(Pattern, SimpleClassLabel, SimpleClassLabel) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter
-
Constructor.
- ClassLabelFromPatternFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
-
Parameterization class.
- classLabelIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter
-
The index of the label to be used as class label, null if no class label is
specified.
- classLabelIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFilter.Parameterizer
-
The index of the label to be used as class label, null if no class label
is specified.
- classListEditor - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.AdjustingEditor
-
The class list editor
- ClassListEditor() - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.ClassListEditor
-
Constructor.
- ClassListParameter<C> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters
-
Parameter class for a parameter specifying a list of class names.
- ClassListParameter(OptionID, Class<?>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassListParameter
-
Constructs a class list parameter with the given optionID and restriction
class.
- ClassListParameter(OptionID, Class<?>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassListParameter
-
Constructs a class list parameter with the given optionID and restriction
class.
- ClassListParameterConfigurator - Class in de.lmu.ifi.dbs.elki.gui.configurator
-
Provide a configuration panel to choose classes with the help of a dropdown.
- ClassListParameterConfigurator(ClassListParameter<?>, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.ClassListParameterConfigurator
-
Constructor.
- CLASSLOADER - Static variable in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
-
Class loader.
- CLASSLOADER - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry
-
Class loader
- CLASSLOADER - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner
-
Class loader
- ClassNode(String, String) - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ClassTree.ClassNode
-
Current class name.
- ClassParameter<C> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters
-
Parameter class for a parameter specifying a class name.
- ClassParameter(OptionID, Class<?>, Class<?>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassParameter
-
Constructs a class parameter with the given optionID, restriction class,
and default value.
- ClassParameter(OptionID, Class<?>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassParameter
-
Constructs a class parameter with the given optionID, restriction class,
and optional flag.
- ClassParameter(OptionID, Class<?>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ClassParameter
-
Constructs a class parameter with the given optionID, and restriction
class.
- ClassParameterConfigurator - Class in de.lmu.ifi.dbs.elki.gui.configurator
-
Provide a configuration panel to choose a class with the help of a dropdown.
- ClassParameterConfigurator(ClassParameter<?>, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.ClassParameterConfigurator
-
Constructor.
- classPriority(Class<?>) - Static method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner
-
Get the priority of a class, or its outer class.
- classProbabilities(O, ArrayList<ClassLabel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.classification.KNNClassifier
-
- classProbabilities(Object, ArrayList<ClassLabel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.classification.PriorProbabilityClassifier
-
- classSize(int) - Method in interface de.lmu.ifi.dbs.elki.visualization.style.ClassStylingPolicy
-
Get the number of elements in the styling class.
- classSize(int) - Method in class de.lmu.ifi.dbs.elki.visualization.style.ClusterStylingPolicy
-
- classSize(int) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.SegmentsStylingPolicy
-
- ClassStylingPolicy - Interface in de.lmu.ifi.dbs.elki.visualization.style
-
Styling policy that is based on classes, for example clusters or
labels.
- ClassTree - Class in de.lmu.ifi.dbs.elki.gui.util
-
Build a tree of available classes for use in Swing UIs.
- ClassTree() - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ClassTree
-
Private constructor.
- ClassTree.ClassNode - Class in de.lmu.ifi.dbs.elki.gui.util
-
Tree node representing a single class.
- ClassTree.PackageNode - Class in de.lmu.ifi.dbs.elki.gui.util
-
Tree node representing a single class.
- clazz - Variable in class de.lmu.ifi.dbs.elki.utilities.ELKIBuilder
-
Class to build.
- clazzes - Variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry
-
Loaded classes.
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor
-
- cleanup() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.AbstractStreamingParser
-
- cleanup() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser
-
- cleanup() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
- cleanup() - Method in interface de.lmu.ifi.dbs.elki.datasource.parser.Parser
-
Perform cleanup operations after parsing.
- cleanup() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
-
- cleanup() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.StringParser
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.AbstractDoubleProcessor
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.DoubleMinMaxProcessor
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.KNNProcessor
-
- cleanup(Processor.Instance) - Method in interface de.lmu.ifi.dbs.elki.parallel.processor.Processor
-
Invoke cleanup.
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteDataStoreProcessor
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteDoubleDataStoreProcessor
-
- cleanup(Processor.Instance) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteIntegerDataStoreProcessor
-
- cleanup() - Method in class de.lmu.ifi.dbs.elki.utilities.io.Tokenizer
-
Perform cleanup.
- clear() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.CachedDistanceQuery
-
Clear the distance cache.
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore.StorageAccessor
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDBIDStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDoubleStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDIntegerStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDRecordStore.StorageAccessor
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDStore
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapRecordStore.StorageAccessor
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapStore
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore
-
Clear the storage (resetting it to the default value).
- clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDArrayList
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.FastutilIntOpenHashSetModifiableDBIDs
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.database.ids.KNNHeap
-
Clear the heap.
- clear() - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDBIDs
-
Clear this collection.
- clear() - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDoubleDBIDList
-
Clear the list contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
-
- clear() - Method in class de.lmu.ifi.dbs.elki.gui.util.LogPane
-
Clear the current contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.gui.util.LogPanel
-
Clear the current contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.gui.util.SavedSettingsFile
-
Remove all saved settings.
- clear(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Reset the vector to 0.
- clear(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Reset the matrix to 0.
- clear() - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCache
-
Clears this cache.
- clear() - Method in class de.lmu.ifi.dbs.elki.persistent.MemoryPageFile
-
- clear() - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile
-
Clears this PageFile.
- clear() - Method in interface de.lmu.ifi.dbs.elki.persistent.PageFile
-
Clears this PageFile.
- clear() - Method in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile
-
Clears this PageFile.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray
-
Reset the numeric attribute counter.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.IntegerArray
-
Reset the numeric attribute counter.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleHeap
-
Delete all elements from the heap.
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerHeap
-
Clear the heap contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongHeap
-
Clear the heap contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectHeap
-
Clear the heap contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap
-
Clear the heap.
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerHeap
-
Delete all elements from the heap.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMinHeap
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectHeap
-
Clear the heap contents.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap
-
- clear() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ObjectHeap
-
Delete all elements from the heap.
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.TiedTopBoundedHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.TiedTopBoundedUpdatableHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.UpdatableHeap
-
- clear() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.LayerMap
-
Clear a map
- clear() - Method in class de.lmu.ifi.dbs.elki.visualization.svg.UpdateRunner
-
Clear queue.
- clearAll(DBIDs, WritableDataStore<HashSetModifiableDBIDs>) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent
-
Clear (but reuse) all sets in the given storage.
- clearC(long, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Clear bit number "off" in v.
- clearErrors() - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.AbstractParameterization
-
Clear errors.
- clearI(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Clear bit number "off" in v.
- clickisout - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.CSSHoverClass
-
Consider a click as 'out'?
- CLINK<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
-
CLINK algorithm for complete linkage.
- CLINK(DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CLINK
-
Constructor.
- CLINK.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
-
Parameterization class.
- clinkstep3(DBIDRef, DBIDArrayIter, int, WritableDBIDDataStore, WritableDoubleDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CLINK
-
Third step: Determine the values for P and L
- clinkstep4567(DBIDRef, ArrayDBIDs, DBIDArrayIter, int, WritableDBIDDataStore, WritableDoubleDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CLINK
-
Fourth to seventh step of CLINK: find best insertion
- clinkstep8(DBIDRef, DBIDArrayIter, int, WritableDBIDDataStore, WritableDoubleDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CLINK
-
Update hierarchy.
- clipmax - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster
-
Clipping vectors.
- clipmin - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster
-
Clipping vectors.
- ClipScaling - Class in de.lmu.ifi.dbs.elki.utilities.scaling
-
Scale implementing a simple clipping.
- ClipScaling(Double, Double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.scaling.ClipScaling
-
Constructor.
- ClipScaling.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.scaling
-
Parameterization class.
- clipToMargin(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.CanvasSize
-
Clip a line on the margin (modifies arrays!)
- CLIQUE - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
-
Implementation of the CLIQUE algorithm, a grid-based algorithm to identify
dense clusters in subspaces of maximum dimensionality.
- CLIQUE(int, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.CLIQUE
-
Constructor.
- CLIQUE.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
-
Parameterization class.
- CLIQUESubspace - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique
-
Represents a subspace of the original data space in the CLIQUE algorithm.
- CLIQUESubspace(int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace
-
Creates a new one-dimensional subspace of the original data space.
- CLIQUESubspace(long[]) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace
-
Creates a new k-dimensional subspace of the original data space.
- CLIQUEUnit - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique
-
Represents a unit in the CLIQUE algorithm.
- CLIQUEUnit(CLIQUEUnit, int, double, double, ModifiableDBIDs) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Creates a new k-dimensional unit for the given intervals.
- CLIQUEUnit(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Creates a new one-dimensional unit for the given interval.
- CLISmartHandler - Class in de.lmu.ifi.dbs.elki.logging
-
Handler that handles output to the console with clever formatting.
- CLISmartHandler(OutputStream, OutputStream) - Constructor for class de.lmu.ifi.dbs.elki.logging.CLISmartHandler
-
Constructor
- CLISmartHandler() - Constructor for class de.lmu.ifi.dbs.elki.logging.CLISmartHandler
-
Default constructor using System.out and System.err
- cloneBits() - Method in class de.lmu.ifi.dbs.elki.data.BitVector
-
Returns a copy of the bits currently set in this BitVector.
- cloneDocument(DOMImplementation, Document) - Method in class de.lmu.ifi.dbs.elki.utilities.xml.DOMCloner
-
Deep-clone a document.
- cloneDocument() - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot
-
Clone the SVGPlot document for transcoding.
- cloneForCache(T) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram
-
Clone a data passed to the algorithm for computing the initial size.
- CloneInlineImages - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
Clone an SVG document, inlining temporary and in-memory linked images.
- CloneInlineImages() - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.CloneInlineImages
-
- cloneNode(Document, Node) - Method in class de.lmu.ifi.dbs.elki.utilities.xml.DOMCloner
-
Clone an existing node.
- cloneNode(Document, Node) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.CloneInlineImages
-
- cloneNode(Document, Node) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGCloneVisible
-
- close() - Method in class de.lmu.ifi.dbs.elki.datasource.InputStreamDatabaseConnection
-
- close() - Method in class de.lmu.ifi.dbs.elki.gui.util.LogPane.LogPaneHandler
-
- close() - Method in class de.lmu.ifi.dbs.elki.gui.util.LogPanel.LogPanelHandler
-
- close() - Method in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler
-
Close output streams.
- close() - Method in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Close command - will be IGNORED.
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractPageFile
-
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCache
-
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArray
-
Explicitly close the file.
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile
-
Closes this file.
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskUpperTriangleMatrix
-
Close the matrix file.
- close() - Method in interface de.lmu.ifi.dbs.elki.persistent.PageFile
-
Closes this file.
- close() - Method in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile
-
Closes this file.
- close() - Method in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput
-
- close() - Method in class de.lmu.ifi.dbs.elki.result.textwriter.SingleStreamOutput
-
- close() - Method in interface de.lmu.ifi.dbs.elki.result.textwriter.StreamFactory
-
Close stream factory.
- close() - Method in class de.lmu.ifi.dbs.elki.utilities.io.BufferedLineReader
-
- close() - Method in class de.lmu.ifi.dbs.elki.utilities.io.LineReader
-
- close() - Method in class de.lmu.ifi.dbs.elki.utilities.io.TokenizedReader
-
- close() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow
-
Close the visualizer window.
- close() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.SimpleSVGViewer
-
Close the visualizer window.
- close() - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
-
Close the path.
- closeButton - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
-
Button to close the window
- CloseReinsert - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert
-
Reinsert objects on page overflow, starting with close objects first (even
when they will likely be inserted into the same page again!)
- CloseReinsert(double, SpatialPrimitiveDistanceFunction<?>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.CloseReinsert
-
Constructor.
- CloseReinsert.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert
-
Parameterization class.
- closeStream(PrintStream) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput
-
- closeStream(PrintStream) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.SingleStreamOutput
-
- closeStream(PrintStream) - Method in interface de.lmu.ifi.dbs.elki.result.textwriter.StreamFactory
-
Close the given output stream (Note: when writing to a single stream
output, it will actually not be closed!)
- CLR_BORDER_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
CSS border class of a cluster
- CLR_CLUSTER_CLASS_PREFIX - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
CSS class name for the clusterings.
- CLR_HOVER_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
CSS hover class of a segment cluster
- CLR_UNPAIRED_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
CSS hover class for clusters of hovered segment
- cls - Variable in class de.lmu.ifi.dbs.elki.data.type.SimpleTypeInformation
-
The restriction class we represent.
- clsname - Variable in class de.lmu.ifi.dbs.elki.gui.util.ClassTree.ClassNode
-
Class name.
- clus - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization.Instance
-
Our clustering
- cluster - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.ProjectedEnergy
-
- Cluster<M extends Model> - Class in de.lmu.ifi.dbs.elki.data
-
Generic cluster class, that may or not have hierarchical information.
- Cluster(String, DBIDs, boolean, M) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Full constructor
- Cluster(String, DBIDs, M) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information.
- Cluster(DBIDs, boolean, M) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and name
- Cluster(DBIDs, M) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and name
- Cluster(String, DBIDs, boolean) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and model
- Cluster(String, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and model
- Cluster(DBIDs, boolean) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and name and model
- Cluster(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.data.Cluster
-
Constructor without hierarchy information and name and model
- CLUSTER - Static variable in class de.lmu.ifi.dbs.elki.data.model.ClusterModel
-
Static cluster model that can be shared for all clusters (since the object
doesn't include meta information.
- cluster_dbids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance
-
Storage for cluster contents
- cluster_leads - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance
-
Cluster lead objects
- cluster_map - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance
-
Map clusters to integer cluster numbers.
- clusteralg - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1
-
Clustering algorithm to run.
- CLUSTERAREA - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization.Instance
-
Generic tags to indicate the type of element.
- ClusterCandidate(P3C.Signature) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.ClusterCandidate
-
Constructor.
- clusterCenters(ArrayList<GeneratorInterface>, ClassLabel[]) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain.AssignLabelsByDistance
-
Compute the cluster centers for each cluster.
- ClusterContingencyTable - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
-
Class storing the contingency table and related data on two clusterings.
- ClusterContingencyTable(boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
-
Constructor.
- ClusterContingencyTable.Util - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
-
Utility class.
- clusterData(DBIDs, RangeQuery<O>, WritableDoubleDataStore, WritableDataStore<ModifiableDBIDs>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF
-
This method applies a density based clustering algorithm.
- CLUSTERDISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer
-
Distance function to measure the similarity of clusterings.
- clusterer - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.KMeansOutlierDetection
-
Clustering algorithm to use
- clusterer - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.KMeansOutlierDetection.Parameterizer
-
Clustering algorithm to use
- clusterer - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.SilhouetteOutlierDetection
-
Clustering algorithm to use
- clusterer - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.SilhouetteOutlierDetection.Parameterizer
-
Clustering algorithm to use
- clusterHeight - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance
-
Cluster distances
- CLUSTERHULL - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization.Instance
-
Generic tags to indicate the type of element.
- ClusterHullVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Visualizer for generating an SVG-Element containing the convex hull / alpha
shape of each cluster.
- ClusterHullVisualization(ClusterHullVisualization.Parameterizer) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization
-
Constructor.
- ClusterHullVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Instance.
- ClusterHullVisualization.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Parameterization class.
- clusterids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
Cluster assignment storage.
- clusterids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Cluster assignments.
- clusterIds - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segment
-
The cluster numbers in each ring
- Clustering<M extends Model> - Class in de.lmu.ifi.dbs.elki.data
-
Result class for clusterings.
- Clustering(String, String, List<Cluster<M>>) - Constructor for class de.lmu.ifi.dbs.elki.data.Clustering
-
Constructor with a list of top level clusters
- Clustering(String, String) - Constructor for class de.lmu.ifi.dbs.elki.data.Clustering
-
Constructor for an empty clustering
- clustering - Variable in class de.lmu.ifi.dbs.elki.result.textwriter.naming.SimpleEnumeratingScheme
-
Clustering this scheme is applied to.
- clustering - Variable in class de.lmu.ifi.dbs.elki.visualization.style.ClusterStylingPolicy
-
Clustering in use.
- CLUSTERING_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF.Parameterizer
-
Parameter to specify the algorithm to be used for clustering.
- CLUSTERING_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.KMeansOutlierDetection.Parameterizer
-
Parameter for choosing the clustering algorithm.
- CLUSTERING_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.SilhouetteOutlierDetection.Parameterizer
-
Parameter for choosing the clustering algorithm
- ClusteringAdjustedRandIndexSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the Adjusted Rand Index.
- ClusteringAdjustedRandIndexSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringAdjustedRandIndexSimilarityFunction
-
- ClusteringAdjustedRandIndexSimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- ClusteringAlgorithm<C extends Clustering<? extends Model>> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the
Algorithm-Interface.
- clusteringAlgorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF
-
The clustering algorithm to use.
- clusteringAlgorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF.Parameterizer
-
The clustering algorithm to use.
- ClusteringAlgorithmUtil - Class in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Utility functionality for writing clustering algorithms.
- ClusteringAlgorithmUtil() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithmUtil
-
Private constructor.
- ClusteringBCubedF1SimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the BCubed F1 Index.
- ClusteringBCubedF1SimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringBCubedF1SimilarityFunction
-
- ClusteringBCubedF1SimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- ClusteringDistanceSimilarityFunction - Interface in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Distance and similarity measure for clusterings.
- ClusteringFeature - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch
-
Clustering Feature of BIRCH
- ClusteringFeature(int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.ClusteringFeature
-
Constructor.
- ClusteringFowlkesMallowsSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the Fowlkes-Mallows Index.
- ClusteringFowlkesMallowsSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringFowlkesMallowsSimilarityFunction
-
- ClusteringFowlkesMallowsSimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- ClusteringRandIndexSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the Rand Index.
- ClusteringRandIndexSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringRandIndexSimilarityFunction
-
- ClusteringRandIndexSimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- clusterings - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segments
-
Clusterings
- clusteringsCount - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segments
-
Number of clusterings in comparison
- ClusteringVectorDumper - Class in de.lmu.ifi.dbs.elki.result
-
Output a clustering result in a simple and compact ascii format:
whitespace separated cluster indexes
This format can be read using
ClusteringVectorParser for meta
analysis, or read as clustering using
ExternalClustering.
- ClusteringVectorDumper(File, boolean, String) - Constructor for class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper
-
Constructor.
- ClusteringVectorDumper(File, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper
-
Constructor.
- ClusteringVectorDumper.Parameterizer - Class in de.lmu.ifi.dbs.elki.result
-
Parameterization class.
- ClusteringVectorParser - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
- ClusteringVectorParser(CSVReaderFormat) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
Constructor.
- ClusteringVectorParser.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Parameterization class.
- ClusterIntersectionSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the intersection size.
- ClusterIntersectionSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusterIntersectionSimilarityFunction
-
- ClusterIntersectionSimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- ClusterJaccardSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Measure the similarity of clusters via the Jaccard coefficient.
- ClusterJaccardSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusterJaccardSimilarityFunction
-
- ClusterJaccardSimilarityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster
-
Parameterization class.
- CLUSTERMEAN - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterParallelMeanVisualization.Instance
-
Generic tags to indicate the type of element.
- ClusterMeanVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Visualize the mean of a KMeans-Clustering
- ClusterMeanVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterMeanVisualization
-
Constructor.
- ClusterMeanVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Instance.
- ClusterModel - Class in de.lmu.ifi.dbs.elki.data.model
-
Generic cluster model.
- ClusterModel() - Constructor for class de.lmu.ifi.dbs.elki.data.model.ClusterModel
-
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Instance
-
Cluster order.
- ClusterOrder - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics
-
Class to store the result of an ordering clustering algorithm such as OPTICS.
- ClusterOrder(DBIDs, String, String) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.ClusterOrder
-
Constructor
- ClusterOrder(String, String, ArrayModifiableDBIDs, WritableDoubleDataStore, WritableDBIDDataStore) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.ClusterOrder
-
Constructor
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSHeap.Instance
-
Output cluster order.
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSList.Instance
-
Output cluster order.
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance
-
Cluster order.
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance
-
Cluster order.
- clusterOrder - Variable in class de.lmu.ifi.dbs.elki.visualization.projector.OPTICSProjector
-
Cluster order result
- CLUSTERORDER - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary
-
Clusterorder
- ClusterOrderVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Cluster order visualizer: connect objects via the spanning tree the cluster
order represents.
- ClusterOrderVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterOrderVisualization
-
Constructor.
- ClusterOrderVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Instance
- ClusterOutlineVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster
-
Generates a SVG-Element that visualizes the area covered by a cluster.
- ClusterOutlineVisualization(ClusterOutlineVisualization.Parameterizer) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization
-
Constructor.
- ClusterOutlineVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster
-
Instance
- ClusterOutlineVisualization.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster
-
Parameterization class.
- ClusterPairSegmentAnalysis - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments
-
Evaluate clustering results by building segments for their pairs: shared
pairs and differences.
- ClusterPairSegmentAnalysis() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.ClusterPairSegmentAnalysis
-
Constructor.
- ClusterParallelMeanVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster
-
Generates a SVG-Element that visualizes cluster means.
- ClusterParallelMeanVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterParallelMeanVisualization
-
Constructor.
- ClusterParallelMeanVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster
-
Instance.
- clusterRandom - Variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection
-
Random generator used for initializing cluster generators.
- clusterRandom - Variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection.Parameterizer
-
Random generator used for initializing cluster generators.
- clusters - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Instance
-
Store the elements per cluster.
- clusters - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansMinusMinus.Instance
-
Cluster storage.
- clusters - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segments
-
Clusters
- ClusterStarVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Visualize the mean of a KMeans-Clustering using stars.
- ClusterStarVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterStarVisualization
-
Constructor.
- ClusterStarVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
-
Instance.
- ClusterStyleAction - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.actions
-
Actions to use clusterings for styling.
- ClusterStyleAction() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction
-
Constructor.
- ClusterStyleAction.SetStyleAction - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.actions
-
- ClusterStylingPolicy - Class in de.lmu.ifi.dbs.elki.visualization.style
-
Styling policy based on cluster membership.
- ClusterStylingPolicy(Clustering<?>, StyleLibrary) - Constructor for class de.lmu.ifi.dbs.elki.visualization.style.ClusterStylingPolicy
-
Constructor.
- ClustersWithNoiseExtraction - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
-
Extraction of a given number of clusters with a minimum size, and noise.
- ClustersWithNoiseExtraction(HierarchicalClusteringAlgorithm, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ClustersWithNoiseExtraction
-
Constructor.
- ClustersWithNoiseExtraction.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
-
Instance for a single data set.
- ClustersWithNoiseExtraction.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
-
Parameterization class.
- cmap - Variable in class de.lmu.ifi.dbs.elki.visualization.style.ClusterStylingPolicy
-
Map from cluster objects to color offsets.
- CNAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.ColoredHistogramVisualizer
-
Name for this visualizer.
- cnum - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansAnnulus.Instance
-
Sorted neighbors
- cnum - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansExponion.Instance
-
Sorted neighbors
- cnum - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansSort.Instance
-
Sorted neighbors
- co - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepScanPosition
-
Cluster order
- co - Variable in class de.lmu.ifi.dbs.elki.visualization.opticsplot.OPTICSPlot
-
The result to plot.
- code - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node
-
Position code
- coeff - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
-
The matrix of coefficients.
- coefficient(double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.PearsonCorrelation
-
Compute the Pearson product-moment correlation coefficient for two
FeatureVectors.
- coefficient(NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.math.PearsonCorrelation
-
Compute the Pearson product-moment correlation coefficient for two
NumberVectors.
- coefficientOfDetermination() - Method in class de.lmu.ifi.dbs.elki.math.statistics.MultipleLinearRegression
-
Returns the coefficient of determination
- COF<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof
-
Connectivity-based Outlier Factor (COF).
- COF(int, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.COF
-
Constructor.
- COF.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof
-
Parameterization class.
- col - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.IntegerRankTieNormalization.Sorter
-
Column to use for sorting.
- col - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
-
Encodes column permutations, column j is at position col[j].
- col - Variable in class de.lmu.ifi.dbs.elki.result.CollectionResult
-
The collection represented.
- colcard - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Cardinalities.
- colDim - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering
-
Column dimensionality.
- colIDs - Variable in class de.lmu.ifi.dbs.elki.data.model.BiclusterModel
-
The column numbers included in the Bicluster.
- collect(int, int[], int, int) - Method in interface de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree.Collector
-
Collect a single frequent itemset
- collectByCover(DBIDRef, ModifiableDoubleDBIDList, double, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree
-
Collect all elements with respect to a new routing object.
- collectChildren(HDBSCANHierarchyExtraction.TempCluster, Clustering<DendrogramModel>, HDBSCANHierarchyExtraction.TempCluster, Cluster<DendrogramModel>, boolean) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Instance
-
Recursive flattening of clusters.
- collectFactorys(MergedParameterization, Pattern) - Static method in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer
-
Collect and instantiate all visualizer factories.
- CollectionFromRelation(Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.CollectionFromRelation
-
Constructor.
- CollectionResult<O> - Class in de.lmu.ifi.dbs.elki.result
-
Simple 'collection' type of result.
- CollectionResult(String, String, Collection<O>, Collection<String>) - Constructor for class de.lmu.ifi.dbs.elki.result.CollectionResult
-
Constructor
- CollectionResult(String, String, Collection<O>) - Constructor for class de.lmu.ifi.dbs.elki.result.CollectionResult
-
Constructor
- colM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Means.
- color - Variable in class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve
-
Suggested color (number).
- COLOR - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary
-
Color
- COLOR_AXIS_LABEL - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for a typical axis label
- COLOR_AXIS_LINE - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for a typical axis
- COLOR_AXIS_MINOR_TICK - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for a typical axis tick mark
- COLOR_AXIS_TICK - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for a typical axis tick mark
- COLOR_DEFAULT_VALUE - Static variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable
-
Color for parameters having a default value.
- COLOR_INCOMPLETE - Static variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable
-
Color for parameters that are not optional and not yet specified.
- COLOR_KEY_BACKGROUND - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for the background of the key box
- COLOR_KEY_LABEL - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for a label in the key part
- COLOR_LINE_COLORS - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
List of line colors
- COLOR_OPTIONAL - Static variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable
-
Color for optional parameters (with no default value)
- COLOR_PAGE_BACKGROUND - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Named color for the page background
- COLOR_PLOT_BACKGROUND - Static variable in interface de.lmu.ifi.dbs.elki.visualization.colors.ColorLibrary
-
Background color for plot area
- COLOR_SYNTAX_ERROR - Static variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable
-
Color for parameters with an invalid value.
- ColoredHistogramVisualizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram
-
Generates a SVG-Element containing a histogram representing the distribution
of the database's objects.
- ColoredHistogramVisualizer(ColoredHistogramVisualizer.Parameterizer) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.ColoredHistogramVisualizer
-
Constructor.
- ColoredHistogramVisualizer.Instance<NV extends NumberVector> - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram
-
Instance
- ColoredHistogramVisualizer.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram
-
Parameterization class.
- ColorfulRenderer() - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.ColorfulRenderer
-
Constructor.
- ColorLibrary - Interface in de.lmu.ifi.dbs.elki.visualization.colors
-
Color scheme interface
- colorLookupStylesheet - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil
-
CSS Stylesheet from Javax, to parse color values.
- colorMultiply(int, double, boolean) - Method in class de.lmu.ifi.dbs.elki.application.experiments.VisualizeGeodesicDistances
-
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.colors.ListBasedColorLibrary
-
Array of color names.
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.opticsplot.OPTICSPlot
-
Color adapter to use
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.Parallel3DRenderer
-
Color table.
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.ClusterStylingPolicy
-
Colors
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.DashedLineStyleLibrary
-
The style library we use for colors
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.SolidLineStyleLibrary
-
Reference to the color library.
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.CircleMarkers
-
Color library
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.MinimalMarkers
-
Color library
- colors - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.PrettyMarkers
-
Color library
- COLORSET - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary
-
Color set
- colorset - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.SegmentsStylingPolicy
-
Color library (only used in compatibility mode)
- colorToString(Color) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil
-
Convert a color name from an AWT color object to CSS syntax
Note: currently only RGB (from ARGB order) are supported.
- colorToString(int) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil
-
Convert a color name from an integer RGB color to CSS syntax
Note: currently only RGB (from ARGB order) are supported.
- cols - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Row and column bitmasks.
- cols - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.NoMissingValuesFilter
-
Number of columns
- colsBitsetToIDs(BitSet) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering
-
Convert a bitset into integer column ids.
- colsBitsetToIDs(long[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering
-
Convert a bitset into integer column ids.
- colSep - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat
-
Stores the column separator pattern
- colSep - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat.Parameterizer
-
Stores the column separator pattern
- colSum(int) - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrix
-
The number of instances present in the specified column.
- column - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.ChangePoint
-
Column id.
- column - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.OfflineChangePointDetectionAlgorithm.Instance
-
Raw data column.
- column - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamConversionFilter
-
The column to filter.
- column - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter
-
The column to filter.
- COLUMN_SEPARATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat.Parameterizer
-
- columnnames - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Column names.
- columnnr - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.OfflineChangePointDetectionAlgorithm.Instance
-
Current column number.
- columnPackedCopy(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Make a one-dimensional column packed copy of the internal array.
- columns - Variable in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle
-
Storing the real contents.
- columns - Static variable in class de.lmu.ifi.dbs.elki.gui.util.ParametersModel
-
Column headers in model
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.CentroidLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.CompleteLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.FlexibleBetaLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.GroupAverageLinkage
-
- combine(int, double, int, double, int, double) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.Linkage
-
Compute combined linkage for two clusters.
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.MedianLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.MinimumVarianceLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.SingleLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.WardLinkage
-
- combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.WeightedAverageLinkage
-
- combine(double[]) - Method in interface de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVoting
-
Combine scores function.
- combine(double[], int) - Method in interface de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVoting
-
Combine scores function.
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative
-
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMax
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMax
-
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMean
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMean
-
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian
-
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMin
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMin
-
- combine(double[]) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative
-
- combine(double[], int) - Method in class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative
-
- combine(int, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.HalfPosPositions
-
- combine(int, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.HalfWidthPositions
-
- combine(int, int, double) - Method in interface de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.Positions
-
Combine two objects, and return the new X coordinate.
- combine(int, double, int, double, int, double) - Method in enum tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3.Linkage
-
- combine(int, double, int, double, int, double) - Method in enum tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4.Linkage
-
- CombinedInsertionStrategy - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert
-
Use two different insertion strategies for directory and leaf nodes.
- CombinedInsertionStrategy(InsertionStrategy, InsertionStrategy) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy
-
Constructor.
- CombinedInsertionStrategy.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert
-
Parameterization class.
- CombinedIntGenerator - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.range
-
Combine multiple ranges.
- CombinedIntGenerator(IntGenerator...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.range.CombinedIntGenerator
-
Constructor.
- CombinedIntGenerator(Collection<IntGenerator>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.range.CombinedIntGenerator
-
Constructor.
- CombinedTypeInformation - Class in de.lmu.ifi.dbs.elki.data.type
-
Class that combines multiple type restrictions into one using an "and" operator.
- CombinedTypeInformation(TypeInformation...) - Constructor for class de.lmu.ifi.dbs.elki.data.type.CombinedTypeInformation
-
Constructor.
- combineRecursive(IntArrayList, int, short[], AggarwalYuEvolutionary.Individuum, AggarwalYuEvolutionary.Individuum) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch
-
Recursive method to build all possible gene combinations using positions
in r.
- comboBox - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.DropdownEditor
-
Combo box to use
- commandLine - Variable in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI
-
Command line output field.
- COMMENT - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering
-
The comment character.
- COMMENT - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.ExternalDoubleOutlierScore
-
The comment character.
- comment - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat
-
Comment pattern.
- comment - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat.Parameterizer
-
Comment pattern.
- comment - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.StringParser
-
Comment pattern.
- comment - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.StringParser.Parameterizer
-
Comment pattern.
- comment - Variable in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Buffer for comment data to output.
- comment - Variable in class de.lmu.ifi.dbs.elki.utilities.io.TokenizedReader
-
Comment pattern.
- COMMENT_CHAR - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceLoader
-
Comment character
- COMMENT_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat.Parameterizer
-
Comment pattern.
- COMMENT_PATTERN - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat
-
Default pattern for comments.
- COMMENT_PATTERN - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.LibSVMFormatParser
-
Comment pattern.
- COMMENT_PREFIX - Static variable in class de.lmu.ifi.dbs.elki.gui.util.SavedSettingsFile
-
Comment prefix
- commentPrint(Object) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print an object into the comments section
- commentPrint(CharSequence) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print an object into the comments section
- commentPrintLn(CharSequence) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print an object into the comments section with trailing newline.
- commentPrintLn(Object) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print an object into the comments section with trailing newline.
- commentPrintLn() - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print a newline into the comments section.
- commentPrintSeparator() - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Print a separator line in the comments section.
- COMMENTSEP - Static variable in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
Comment separator line.
- CommonConstraints - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints
-
Class storing a number of very common constraints.
- CommonConstraints() - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints
-
- commonPreferenceVectors - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.DiSHClusterOrder
-
Preference vectors.
- commonPreferenceVectors - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance
-
Shared preference vectors.
- commonPreferenceVectors - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance
-
Shared preference vectors.
- CompactCircularMSTLayout3DPC - Class in de.lmu.ifi.dbs.elki.visualization.parallel3d.layout
-
Simple circular layout based on the minimum spanning tree.
- CompactCircularMSTLayout3DPC(DependenceMeasure) - Constructor for class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC
-
Constructor.
- CompactCircularMSTLayout3DPC.Node - Class in de.lmu.ifi.dbs.elki.visualization.parallel3d.layout
-
Node class for this layout.
- CompactCircularMSTLayout3DPC.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization.parallel3d.layout
-
Parameteriation class.
- ComparableMaxHeap<K extends java.lang.Comparable<? super K>> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Binary heap for primitive types.
- ComparableMaxHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap
-
Constructor, with default size.
- ComparableMaxHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap
-
Constructor, with given minimum size.
- ComparableMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Unsorted iterator - in heap order.
- ComparableMinHeap<K extends java.lang.Comparable<? super K>> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Binary heap for primitive types.
- ComparableMinHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap
-
Constructor, with default size.
- ComparableMinHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap
-
Constructor, with given minimum size.
- ComparableMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Unsorted iterator - in heap order.
- comparator - Variable in class de.lmu.ifi.dbs.elki.result.OrderingFromDataStore
-
Comparator to use when sorting
- comparator - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
-
Comparator
- comparator - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
-
Comparator
- comparator - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap
-
The comparator.
- ComparatorMaxHeap<K> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Binary heap for primitive types.
- ComparatorMaxHeap(Comparator<? super K>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
-
Constructor, with default size.
- ComparatorMaxHeap(int, Comparator<? super K>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
-
Constructor, with given minimum size.
- ComparatorMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Unsorted iterator - in heap order.
- ComparatorMinHeap<K> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Binary heap for primitive types.
- ComparatorMinHeap(Comparator<? super K>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
-
Constructor, with default size.
- ComparatorMinHeap(int, Comparator<? super K>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
-
Constructor, with given minimum size.
- ComparatorMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap
-
Unsorted iterator - in heap order.
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Instance
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationResult.Sorter
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.GeneralizedOPTICS.Instance
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance.Sorter
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance
-
- compare(SpatialComparable, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMaxComparator
-
- compare(SpatialComparable, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMeanComparator
-
- compare(SpatialComparable, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMinComparator
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.data.VectorUtil.SortDBIDsBySingleDimension
-
- compare(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.data.VectorUtil.SortVectorsBySingleDimension
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.AscendingByDoubleDataStore
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.AscendingByDoubleDataStoreAndId
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.AscendingByIntegerDataStore
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByDoubleDataStore
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByDoubleDataStoreAndId
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByIntegerDataStore
-
- compare(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Compare two DBIDs, for sorting.
- compare(DBIDRef, DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Compare two DBIDs.
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- compare(IntegerDBIDVar, int, IntegerDBIDVar, int, Comparator<? super DBIDRef>) - Static method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDArrayQuickSort
-
Compare two elements.
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.AscendingByDoubleRelation
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.DescendingByDoubleRelation
-
- compare(int, int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.IntegerRankTieNormalization.Sorter
-
- compare(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DecreasingVectorIter
-
- compare(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.IncreasingVectorIter
-
- compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.CountSortAccesses
-
- compare(DAFile, DAFile) - Method in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.WorstCaseDistComparator
-
- compare(SpatialComparable, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.BinarySplitSpatialSorter.Sorter
-
- compare(long, long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Compare two bitsets.
- compare(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Compare two bitsets.
- compare(int, int) - Method in class tutorial.clustering.SameSizeKMeansAlgorithm.PreferenceComparator
-
- compareGreater(T, int, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.QuickSelect.Adapter
-
Compare two elements.
- compareLexicographical(Itemset, Itemset) - Static method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Itemset
-
Robust compare using the iterators, lexicographical only!
- comparePackageClass(Class<?>, Class<?>) - Static method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner
-
Compare two classes, by package name first.
- compareSwappedTo(DoubleDoublePair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair
-
Implementation of comparableSwapped interface, sorting by second then
first.
- compareSwappedTo(DoubleIntPair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleIntPair
-
Implementation of comparableSwapped interface, sorting by second then
first.
- compareSwappedTo(IntDoublePair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntDoublePair
-
Implementation of comparableSwapped interface, sorting by second then
first.
- compareSwappedTo(IntIntPair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntIntPair
-
Implementation of comparableSwapped interface, sorting by second then
first.
- compareTo(CASHInterval) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval
-
- compareTo(ORCLUS<V>.ProjectedEnergy) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.ProjectedEnergy
-
Compares this object with the specified object for order.
- compareTo(Border) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util.Border
-
- compareTo(DeLiClu.SpatialObjectPair) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair
-
Compares this object with the specified object for order.
- compareTo(OPTICSHeapEntry) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSHeapEntry
-
- compareTo(PROCLUS.DoubleIntInt) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.DoubleIntInt
-
- compareTo(AssociationRule) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.AssociationRule
-
- compareTo(Itemset) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset
-
- compareTo(Itemset) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Itemset
-
- compareTo(Itemset) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset
-
- compareTo(Itemset) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset
-
- compareTo(Itemset) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SparseItemset
-
- compareTo(KNNJoin<V, N, E>.Task) - Method in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin.Task
-
- compareTo(HilOut.HilFeature) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.HilFeature
-
- compareTo(AggarwalYuEvolutionary.Individuum) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum
-
- compareTo(ClassLabel) - Method in class de.lmu.ifi.dbs.elki.data.HierarchicalClassLabel
-
Compares two HierarchicalClassLabels.
- compareTo(ClassLabel) - Method in class de.lmu.ifi.dbs.elki.data.SimpleClassLabel
-
- compareTo(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBID
-
Compare two DBIDs for ordering.
- compareTo(DoubleDBIDPair) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPair
-
- compareTo(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID
-
- compareTo(Segment) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segment
-
- compareTo(MTreeSearchCandidate) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query.MTreeSearchCandidate
-
- compareTo(DistanceEntry<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.distribution.DistanceEntry
-
Compares this object with the specified object for order.
- compareTo(RStarTreeKNNQuery.DoubleDistanceEntry) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery.DoubleDistanceEntry
-
- compareTo(PartialVAFile.PartialVACandidate) - Method in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.PartialVACandidate
-
- compareTo(EigenPair) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.EigenPair
-
Compares this object with the specified object for order.
- compareTo(HilbertSpatialSorter.HilbertRef) - Method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter.HilbertRef
-
- compareTo(DoubleDoublePair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair
-
Implementation of comparable interface, sorting by first then second.
- compareTo(DoubleIntPair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleIntPair
-
Implementation of comparable interface, sorting by first then second.
- compareTo(DoubleObjPair<O>) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleObjPair
-
- compareTo(IntDoublePair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntDoublePair
-
Implementation of comparable interface, sorting by first then second.
- compareTo(IntIntPair) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntIntPair
-
Implementation of comparable interface, sorting by first then second.
- compareTo(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask
-
- COMPARISON_DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LoOP.Parameterizer
-
The distance function to determine the reachability distance between
database objects.
- comparisonDistanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LoOP
-
Distance function for comparison set.
- comparisonDistanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LoOP.Parameterizer
-
Preprocessor Step 2.
- compat - Variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler
-
Compatibility mode.
- compat - Variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler.Parameterizer
-
Compatibility mode
- COMPAT_ID - Static variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler.Parameterizer
-
Parameter for compatibility mode.
- complete() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationBuilder
-
Finalize the result.
- complete() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.ThumbnailRegistryEntry.InternalParsedURLData
-
- completed - Variable in class de.lmu.ifi.dbs.elki.logging.progress.IndefiniteProgress
-
Store completion flag.
- completedTextures - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.Parallel3DRenderer
-
Number of completely rendered textures.
- CompleteLinkage - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage
-
Complete-linkage ("maximum linkage") clustering method.
- CompleteLinkage() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage.CompleteLinkage
-
- CompleteLinkage.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.linkage
-
Class parameterizer.
- component - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.DispatchingPanel
-
Component to dispatch to.
- component - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer
-
Component the ratio applies to.
- componentResized(ComponentEvent) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer
-
React to a component resize event.
- compress - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.TextWriterPanel
-
Compression option.
- compute() - Method in class de.lmu.ifi.dbs.elki.math.geometry.AlphaShape
-
- computeABOF(KernelMatrix, DBIDRef, DBIDArrayIter, DBIDArrayIter, MeanVariance) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD
-
Compute the exact ABOF value.
- computeAffinityMatrix(Relation<T>, double) - Method in interface de.lmu.ifi.dbs.elki.algorithm.projection.AffinityMatrixBuilder
-
Compute the affinity matrix.
- computeAffinityMatrix(Relation<T>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.GaussianAffinityMatrixBuilder
-
- computeAffinityMatrix(Relation<T>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder
-
- computeAffinityMatrix(Relation<T>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
- computeAffinityMatrix(Relation<T>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.PerplexityAffinityMatrixBuilder
-
- computeAttractiveForces(double[], AffinityMatrix, double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE
-
- computeAverageChainingDistances(KNNQuery<O>, DistanceQuery<O>, DBIDs, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.COF
-
Computes the average chaining distance, the average length of a path
through the given set of points to each target.
- computeAverageDistInSet() - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics.RandomProjectedNeighborsAndDensities
-
Compute for each point a density estimate as inverse of average distance to
a point in a projected set
- computeBadMedoids(ArrayDBIDs, ArrayList<PROCLUS.PROCLUSCluster>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
-
Computes the bad medoids, where the medoid of a cluster with less than the
specified threshold of objects is bad.
- computeBivariateRanks(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HoeffdingsDDependenceMeasure
-
Compute bivariate ranks.
- computeBounds(NumberVector[]) - Static method in class de.lmu.ifi.dbs.elki.data.uncertain.AbstractUncertainObject
-
Compute the bounding box for some samples.
- computeCBLOFs(Relation<O>, NumberVectorDistanceFunction<? super O>, WritableDoubleDataStore, DoubleMinMax, List<? extends Cluster<MeanModel>>, List<? extends Cluster<MeanModel>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF
-
Compute the CBLOF scores for all the data.
- computeCenterofMass(int, double[][], int, int) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE.QuadTree
-
Computer the center of mass.
- computeCentroid(double[], Relation<? extends NumberVector>, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
-
Recompute the centroid of a set.
- computeCentroids(int, List<V>, List<ClassLabel>, Map<ClassLabel, IntList>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.LinearDiscriminantAnalysisFilter
-
Compute the centroid for each class.
- computeClusterQuality(int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC
-
Computes the quality of a cluster based on its size and number of relevant
attributes, as described via the μ-function from the paper.
- computeClusters(Relation<V>, DiSH.DiSHClusterOrder) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH
-
Computes the hierarchical clusters according to the cluster order.
- computeCOFScores(KNNQuery<O>, DBIDs, DoubleDataStore, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.COF
-
Compute Connectivity outlier factors.
- computeColResidue(double[][], int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Computes the mean column residue of the given col.
- computeConfidence(int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering
-
Estimate the confidence probability of a clustering.
- computeConvexHull() - Method in class de.lmu.ifi.dbs.elki.math.geometry.FilteredConvexHull2D
-
Compute the convex hull.
- computeConvexHull() - Method in class de.lmu.ifi.dbs.elki.math.geometry.GrahamScanConvexHull2D
-
Compute the convex hull.
- computeCoreDists(DBIDs, KNNQuery<O>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN
-
Compute the core distances for all objects.
- computeCostDifferential(DBIDRef, int, CLARANS.Assignment) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS.Assignment
-
Compute the reassignment cost, for one swap.
- computeCostDifferential(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARANS.Assignment
-
Compute the reassignment cost, for one swap.
- computeDCG(ScoreEvaluation.Predicate<? super I>, I) - Static method in class de.lmu.ifi.dbs.elki.evaluation.scores.DCGEvaluation
-
Compute the DCG given a set of positive IDs and a sorted list of entries,
which may include ties.
- computeDCovar(double[], double[], int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure
-
Computes the distance covariance for two axis.
- computeDensity(DoubleDBIDList, DoubleDBIDListIter, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.ReferenceBasedOutlierDetection
-
Computes the density of an object.
- computeDiffs(List<CLIQUESubspace>, int[], int[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.CLIQUE
-
The specified sorted list of dense subspaces is divided into the selected
set I and the pruned set P.
- computeDimensionMap(List<PROCLUS.DoubleIntInt>, int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
-
Compute the dimension map.
- computeDistanceMatrix(AbstractMTree<?, N, E, ?>, N) - Static method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.AbstractMTreeSplit
-
Compute the pairwise distances in the given node.
- computeDistances(ModifiableDoubleDBIDList, DBIDIter, DistanceQuery<O>, Relation<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance
-
Compute the distances to the neighbor objects.
- computeDistances(NumberArrayAdapter<?, A>, A) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure
-
Compute the double-centered delta matrix.
- computeDistanceVector(NumberVector, Relation<? extends NumberVector>, PrimitiveDistanceQuery<? super NumberVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.ReferenceBasedOutlierDetection
-
Computes for each object the distance to one reference point.
- computeExplainedVariance(double[], int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.AutotuningPCA
-
Compute the explained variance for a filtered EigenPairs.
- computeExtend(int, double[][], int, int) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE.QuadTree
-
Compute the bounding box of a data set.
- computeFirstCover(boolean) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.distribution.Assignments
-
Compute the covering radius of the first assignment.
- computeFuzzyMembership(Relation<V>, ArrayList<P3C.Signature>, ModifiableDBIDs, WritableDataStore<double[]>, List<MultivariateGaussianModel>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C
-
Computes a fuzzy membership with the weights based on which cluster cores
each data point is part of.
- computeGradient(AffinityMatrix, double[][], double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE
-
- computeGradient(AffinityMatrix, double[][], double, double[][], double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.SNE
-
Compute the gradients.
- computeGradient(AffinityMatrix, double[][], double, double[][], double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.TSNE
-
Compute the gradients.
- computeGridBaseOffsets() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Compute the grid base offset.
- computeH(DBIDRef, DoubleDBIDListIter, double[], double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.SOS
-
Compute H (observed perplexity) for row i, and the row pij_i.
- computeH(int, double[], double[], double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.GaussianAffinityMatrixBuilder
-
Compute H (observed perplexity) for row i, and the row pij_i.
- computeH(DoubleArray, double[], double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Compute H (observed perplexity) for row i, and the row pij_i.
- computeHeight() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Computes the height of this RTree.
- computeHeight() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
Returns the height of this FlatRTree.
- computeHeight() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.NonFlatRStarTree
-
Computes the height of this RTree.
- computeIDOS(DBIDs, KNNQuery<O>, DoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS
-
Computes all IDOS scores.
- computeIDs(DBIDs, KNNQuery<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS
-
Computes all IDs
- computeIncreaseArea(double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.RectangleArranger
-
- computeINFLO(Relation<O>, ModifiableDBIDs, KNNQuery<O>, WritableDataStore<ModifiableDBIDs>, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.INFLO
-
Compute the final INFLO scores.
- ComputeKNNOutlierScores<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.application.greedyensemble
-
Application that runs a series of kNN-based algorithms on a data set, for
building an ensemble in a second step.
- ComputeKNNOutlierScores(InputStep, DistanceFunction<? super O>, IntGenerator, ByLabelOutlier, File, ScalingFunction, Pattern, int) - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores
-
Constructor.
- ComputeKNNOutlierScores.Parameterizer<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.application.greedyensemble
-
Parameterization class.
- computeLargeClusterCBLOF(O, NumberVectorDistanceFunction<? super O>, NumberVector, Cluster<MeanModel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF
-
- computeLocalModel(DBIDRef, DoubleDBIDList, Relation<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate
-
Method to compute the actual data model.
- computeLocalModel(DBIDRef, DoubleDBIDList, Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate
-
COPAC model computation
- computeLocalModel(DBIDRef, DoubleDBIDList, Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.FourCNeighborPredicate
-
- computeLocalModel(DBIDRef, DoubleDBIDList, Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.PreDeConNeighborPredicate
-
- computeLOFs(KNNQuery<O>, DBIDs, DoubleDataStore, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.FlexibleLOF
-
Computes the Local outlier factor (LOF) of the specified objects.
- computeLOFScore(KNNQuery<O>, DBIDRef, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOF
-
Compute a single LOF score.
- computeLOFScores(KNNQuery<O>, DBIDs, DoubleDataStore, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOF
-
Compute local outlier factors.
- computeLRD(KNNQuery<O>, DBIDIter) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOF
-
Compute a single local reachability distance.
- computeLRDs(KNNQuery<O>, DBIDs, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.FlexibleLOF
-
Computes the local reachability density (LRD) of the specified objects.
- computeLRDs(KNNQuery<O>, DBIDs, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOF
-
Compute local reachability distances.
- computeM_current(DBIDs, DBIDs, DBIDs, Random) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
-
Computes the set of medoids in current iteration.
- computeMAD(double[], int, double, double[]) - Static method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MADDistributionEstimator
-
Compute the median absolute deviation from median.
- computeMAD(double[], int, double) - Static method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MADDistributionEstimator
-
Compute the median absolute deviation from median.
- computeMaxHeight() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationResult
-
Compute the maximum height of nodes.
- computeMBR() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode
-
Recomputing the MBR is rather expensive.
- computeMean() - Method in interface de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorInterface
-
Get the cluster mean vector.
- computeMean() - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster
-
- computeMean() - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorStatic
-
- computeMeans(List<CLIQUESubspace>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.CLIQUE
-
The specified sorted list of dense subspaces is divided into the selected
set I and the pruned set P.
- computeMeanSquaredDeviation(double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Compute the mean square residue.
- computeMinMax(Relation<? extends NumberVector>) - Static method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil
-
Determines the minimum and maximum values in each dimension of all objects
stored in the given database.
- computeMinMax(Iterable<? extends SpatialComparable>) - Static method in interface de.lmu.ifi.dbs.elki.math.spacefillingcurves.SpatialSorter
-
Compute the minimum and maximum for each dimension.
- computeNDCG(ScoreEvaluation.Predicate<? super I>, I) - Static method in class de.lmu.ifi.dbs.elki.evaluation.scores.NDCGEvaluation
-
Compute the DCG given a set of positive IDs and a sorted list of entries,
which may include ties.
- computeNeighborhoods(Relation<O>, DataStore<SetDBIDs>, ModifiableDBIDs, WritableDataStore<ModifiableDBIDs>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.INFLO
-
Compute the reverse kNN minus the kNN.
- computeNNForRealData(KNNQuery<NumberVector>, Relation<NumberVector>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.HopkinsStatisticClusteringTendency
-
Search nearest neighbors for real data members.
- computeNNForUniformData(KNNQuery<NumberVector>, double[], double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.HopkinsStatisticClusteringTendency
-
Search nearest neighbors for artificial, uniform data.
- computeNormalizedRanks(NumberArrayAdapter<?, A>, A, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
-
Compute ranks of all objects, normalized to [0;1]
(where 0 is the smallest value, 1 is the largest).
- computeOffset(int, int) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskUpperTriangleMatrix
-
Compute the offset within the file.
- ComputeOutlierHistogram - Class in de.lmu.ifi.dbs.elki.evaluation.outlier
-
Compute a Histogram to evaluate a ranking algorithm.
- ComputeOutlierHistogram(Pattern, int, ScalingFunction, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.outlier.ComputeOutlierHistogram
-
Constructor.
- ComputeOutlierHistogram.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.outlier
-
Parameterization class.
- computeOutlierScores(Database, Relation<O>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier
-
computes an outlier score for each object of the database.
- computeOutlierScores(Database, Relation<O>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierDetection
-
- computeOutlierScores(Database, Relation<O>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierScore
-
- computeOutlierScores(KNNQuery<O>, DBIDs, WritableDataStore<double[]>, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS
-
Compute the final KDEOS scores.
- computeOverlap(A, ArrayAdapter<E, A>, long[]) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.AngTanLinearSplit
-
Compute overlap of assignment
- computePDists(Relation<O>, KNNQuery<O>, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LoOP
-
Compute the probabilistic distances used by LoOP.
- computePerDimensionVariances(Relation<? extends NumberVector>, double[], DBIDs) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.SOD
-
Compute the per-dimension variances for the given neighborhood and center.
- computePi(DBIDRef, DoubleDBIDListIter, double[], double, double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.SOS
-
Compute row p[i], using binary search on the kernel bandwidth sigma to
obtain the desired perplexity.
- computePi(int, double[], double[], double, double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.PerplexityAffinityMatrixBuilder
-
Compute row pij[i], using binary search on the kernel bandwidth sigma to
obtain the desired perplexity.
- computePij(double[][], double, double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.GaussianAffinityMatrixBuilder
-
Compute the pij from the distance matrix.
- computePij(DBIDRange, KNNQuery<?>, boolean, int, double[][], int[][], double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder
-
Compute the sparse pij using the nearest neighbors only.
- computePij(DBIDRange, KNNQuery<?>, boolean, int, double[][], int[][], double) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Compute the sparse pij using the nearest neighbors only.
- computePij(double[][], double, double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.PerplexityAffinityMatrixBuilder
-
Compute the pij from the distance matrix.
- computePLOFs(Relation<O>, KNNQuery<O>, WritableDoubleDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LoOP
-
Compute the LOF values, using the pdist distances.
- computePopupBounds(Component, int, int, int, int) - Method in class de.lmu.ifi.dbs.elki.gui.util.TreePopup
-
- computePositions(CompactCircularMSTLayout3DPC.Node, int, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC
-
Compute the layout positions
- computePositions(SimpleCircularMSTLayout3DPC.Node, int, double, double, int) - Static method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.SimpleCircularMSTLayout3DPC
-
Compute the layout positions
- computePrecisionResult(int, SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierPrecisionAtKCurve
-
- computePrecisionResult(SetDBIDs, DBIDIter, DoubleRelation) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierPrecisionRecallCurve
-
- computeProjectionMatrix(List<V>, List<? extends ClassLabel>, int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.AbstractSupervisedProjectionVectorFilter
-
computes the projection matrix
- computeProjectionMatrix(List<V>, List<? extends ClassLabel>, int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.LinearDiscriminantAnalysisFilter
-
- computeQij(double[][], double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.SNE
-
Compute the qij of the solution, and the sum.
- computeQij(double[][], double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.TSNE
-
Compute the qij of the solution, and the sum.
- computeReassignmentCost(DBIDRef, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsFastPAM.Instance
-
Compute the reassignment cost of one swap.
- computeReassignmentCost(DBIDRef, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsFastPAM1.Instance
-
Compute the reassignment cost, for all medoids in one pass.
- computeReassignmentCost(DBIDRef, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPAM.Instance
-
Compute the reassignment cost of one swap.
- computeReassignmentCost(DBIDRef, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPAMReynolds.Instance
-
Compute the reassignment cost, for all medoids in one pass.
- computeReinserts(A, ArrayAdapter<? extends SpatialComparable, ? super A>, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.CloseReinsert
-
- computeReinserts(A, ArrayAdapter<? extends SpatialComparable, ? super A>, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.FarReinsert
-
- computeReinserts(A, ArrayAdapter<? extends SpatialComparable, ? super A>, SpatialComparable) - Method in interface de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.ReinsertStrategy
-
Perform reinsertions.
- computeRemovalCost(int, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPAMReynolds.Instance
-
Compute the cost of removing a medoid just once.
- computeRepulsiveForces(double[], int, double[], BarnesHutTSNE.QuadTree) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE
-
Compute the repulsive forces for a single point
- computeROCAUC(ScoreEvaluation.Predicate<? super I>, I) - Static method in class de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation
-
Compute the area under the ROC curve given a set of positive IDs and a
sorted list of (comparable, ID)s, where the comparable object is used to
decided when two objects are interchangeable.
- computeROCResult(SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierROCCurve
-
- computeROCResult(SetDBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierROCCurve
-
- computeRowResidue(double[][], int, boolean) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate
-
Computes the mean row residue of the given row.
- computeScale(ClusterOrder) - Method in class de.lmu.ifi.dbs.elki.visualization.opticsplot.OPTICSPlot
-
Compute the scale (value range)
- computeScore(DBIDs, DBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.JudgeOutlierScores
-
Evaluate a single outlier score result.
- computeSecondCover(boolean) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.distribution.Assignments
-
Compute the covering radius of the second assignment.
- computeSetsBounds(Relation<V>, int, DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics.RandomProjectedNeighborsAndDensities
-
Create random projections, project points and put points into sets of size
about minSplitSize/2
- computeSigma(int, DoubleArray, double, double, double[]) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Compute row pij[i], using binary search on the kernel bandwidth sigma to
obtain the desired perplexity.
- computeSimilarityMatrix(DependenceMeasure, Relation<? extends NumberVector>) - Static method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.AbstractLayout3DPC
-
Compute a column-wise dependency matrix for the given relation.
- ComputeSimilarityMatrixImage<O> - Class in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix
-
Compute a similarity matrix for a distance function.
- ComputeSimilarityMatrixImage(DistanceFunction<? super O>, ScalingFunction, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage
-
Constructor.
- computeSimilarityMatrixImage(Relation<O>, DBIDIter) - Method in class de.lmu.ifi.dbs.elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage
-
Compute the actual similarity image.
- ComputeSimilarityMatrixImage.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix
-
Parameterization class.
- ComputeSimilarityMatrixImage.SimilarityMatrix - Class in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix
-
Similarity matrix image.
- computeSimplifiedLOFs(DBIDs, KNNQuery<O>, WritableDoubleDataStore, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.SimplifiedLOF
-
Compute the simplified LOF factors.
- computeSimplifiedLRDs(DBIDs, KNNQuery<O>, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.SimplifiedLOF
-
Compute the simplified reachability densities.
- computeSmallClusterCBLOF(O, NumberVectorDistanceFunction<? super O>, List<NumberVector>, Cluster<MeanModel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.CBLOF
-
- computeSmROCResult(SetDBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierSmROCCurve
-
- computeSquaredDistanceMatrix(List<I>, PrimitiveDistanceFunction<? super I>) - Static method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform
-
Compute the squared distance matrix.
- computeSquareSize(double[]) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.BarnesHutTSNE.QuadTree
-
Compute the square size of a bounding box.
- computeStopDistance(List<KNNHeap>) - Method in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin
-
Compute the maximum stop distance.
- computeSubspace(int[], ArrayList<ArrayList<DBIDs>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier
-
Method to get the ids in the given subspace.
- computeSubspaceForGene(short[], ArrayList<ArrayList<DBIDs>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier
-
Get the DBIDs in the current subspace.
- computeSubtreeSizes(DBIDs) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationResult
-
Compute the size of all subtrees.
- computeTau(long, long, double, long, long) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
-
Compute the Tau correlation measure
- computeVolumes(KNNQuery<O>, int, DBIDs, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.VarianceOfVolume
-
Compute volumes
- computeVOVs(KNNQuery<O>, DBIDs, DoubleDataStore, WritableDoubleDataStore, DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.VarianceOfVolume
-
Compute variance of volumes.
- computeWeight(int) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted.LinearWeightedExtendedNeighborhood
-
Compute the weight from the number of steps needed.
- computeWeightMatrix(int, int, int) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HSBHistogramQuadraticDistanceFunction
-
Compute the weight matrix for HSB similarity.
- computeWeightMatrix(int) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.RGBHistogramQuadraticDistanceFunction
-
Compute weight matrix for a RGB color histogram
- computeWeights(CompactCircularMSTLayout3DPC.Node) - Method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC
-
Recursively assign node weights.
- computeWeights(SimpleCircularMSTLayout3DPC.Node) - Method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.SimpleCircularMSTLayout3DPC
-
Recursively assign node weights.
- computeWithinDistances(Relation<? extends NumberVector>, List<? extends Cluster<?>>, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
-
- computeZijs(double[][], int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
-
Compute the z_ij values.
- ConcatenateFilesDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource
-
Database that will loading multiple files, concatenating the results.
- ConcatenateFilesDatabaseConnection(List<File>, Parser, List<ObjectFilter>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ConcatenateFilesDatabaseConnection
-
Constructor.
- ConcatenateFilesDatabaseConnection.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource
-
Parameterization class.
- ConcatIt<O> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.iterator
-
Concatenate multiple iterators.
- ConcatIt(It<? extends O>...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ConcatIt
-
Constructor.
- cond() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition
-
Two norm condition number
- condenseTree(IndexTreePath<E>, Stack<N>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Condenses the tree after deletion of some nodes.
- CONDITION - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory
-
Description for the determination of the preference vector.
- confbase - Static variable in class de.lmu.ifi.dbs.elki.logging.LoggingConfiguration
-
Configuration base
- Confidence - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest
-
Confidence interestingness measure,
\( \tfrac{\text{support}(X \cup Y)}{\text{support}(X)}
= \tfrac{P(X \cap Y)}{P(X)}=P(Y|X) \).
- Confidence() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest.Confidence
-
Constructor.
- CONFIDENCE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.OfflineChangePointDetectionAlgorithm.Parameterizer
-
Mininum confidence.
- config - Static variable in class de.lmu.ifi.dbs.elki.logging.LoggingConfiguration
-
Static instance of the configuration
- configAlpha(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer
-
Get the alpha parameter.
- configBulkLoad(Parameterization) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeFactory.Parameterizer
-
Configure the bulk load parameters.
- configC(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer
-
get the c parameter.
- configD(Parameterization, DistanceFunction<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier.Parameterizer
-
Grab the 'd' configuration option.
- configDelta(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer
-
Configure the delta parameter.
- configDelta(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer
-
Configure the delta parameter.
- configDiSHPreprocessor(Parameterization, double, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Parameterizer
-
- configDistance(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer
-
Configure the distance parameter.
- configEpsilon(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer
-
Configure the epsilon radius parameter.
- configEpsilon(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer
-
Configure the epsilon parameter.
- configEpsilon(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer
-
Configure the epsilon radius parameter.
- CONFIGFILE_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection.Parameterizer
-
Parameter to give the configuration file
- configFilters(Parameterization) - Method in class de.lmu.ifi.dbs.elki.datasource.AbstractDatabaseConnection.Parameterizer
-
Get the filters parameter
- configIndexFactory(Parameterization, Class<?>, Class<?>) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractIndexBasedDistanceFunction.Parameterizer
-
Index factory parameter
- configIndexFactory(Parameterization, Class<?>, Class<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractIndexBasedSimilarityFunction.Parameterizer
-
Get the index factory parameter.
- configK(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer
-
Get the kNN parameter.
- configKappa(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer
-
Configure the kappa parameter.
- configKappa(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer
-
Configure the kappa parameter.
- configLambda(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer
-
Configure the delta parameter.
- configLambda(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer
-
Configure the delta parameter.
- configMinPts(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer
-
Configure the minPts aka "mu" parameter.
- configMinPts(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer
-
Configure the minPts aka "mu" parameter.
- configParser(Parameterization, Class<?>, Class<?>) - Method in class de.lmu.ifi.dbs.elki.datasource.AbstractDatabaseConnection.Parameterizer
-
Get the parser parameter
- ConfiguratorPanel - Class in de.lmu.ifi.dbs.elki.gui.configurator
-
A panel that contains configurators for parameters.
- ConfiguratorPanel() - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
-
Constructor.
- configure(Parameterization) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer
-
- configure(Parameterization) - Method in interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizer
-
Configure the class.
- configurePopup() - Method in class de.lmu.ifi.dbs.elki.gui.util.TreePopup
-
Configure the popup display.
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel
-
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel
-
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.InputTabPanel
-
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.LoggingTabPanel
-
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel
-
- configureStep(Parameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel
-
Configure this step with the given parameters.
- confusion - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrix
-
Holds the confusion matrix.
- ConfusionMatrix - Class in de.lmu.ifi.dbs.elki.evaluation.classification
-
Provides a confusion matrix with some prediction performance measures that
can be derived from a confusion matrix.
- ConfusionMatrix(ArrayList<ClassLabel>, int[][]) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrix
-
Provides a confusion matrix for the given values.
- confusionmatrix - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrixEvaluationResult
-
Holds the confusion matrix.
- ConfusionMatrixEvaluationResult - Class in de.lmu.ifi.dbs.elki.evaluation.classification
-
Provides the prediction performance measures for a classifier based on the
confusion matrix.
- ConfusionMatrixEvaluationResult(ConfusionMatrix, String) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrixEvaluationResult
-
Provides an evaluation based on the given confusion matrix.
- connect() - Method in class de.lmu.ifi.dbs.elki.parallel.ParallelCore
-
Connect to the executor.
- connected - Variable in class de.lmu.ifi.dbs.elki.parallel.ParallelCore
-
Number of connected submitters.
- connectInput(SharedDouble) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.DoubleMinMaxProcessor
-
Connect an input channel.
- connectInput(SharedObject<T>) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteDataStoreProcessor
-
Connect the data source
- connectInput(SharedDouble) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteDoubleDataStoreProcessor
-
Connect the input variable
- connectInput(SharedInteger) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.WriteIntegerDataStoreProcessor
-
Connect the input variable
- connectKNNInput(SharedObject<? extends KNNList>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel.KNNWeightProcessor
-
Connect the input channel.
- connectKNNInput(SharedObject<? extends KNNList>) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.KDistanceProcessor
-
Connect the input channel.
- connectKNNOutput(SharedObject<KNNList>) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.KNNProcessor
-
Connect the output channel.
- connectOutput(SharedDouble) - Method in class de.lmu.ifi.dbs.elki.parallel.processor.AbstractDoubleProcessor
-
Connect the output variable.
- consequent - Variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.AssociationRule
-
Consequent itemset
- conservativeApproximation - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry
-
The conservative approximation.
- conservativeApproximation - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry
-
The conservative approximation.
- conservativeKnnDistanceApproximation(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeNode
-
Determines and returns the conservative approximation for the knn distances
of this node as the maximum of the conservative approximations of all
entries.
- constant - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution.Parameterizer
-
Parameters.
- CONSTANT_ID - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution.Parameterizer
-
Constant value parameter
- ConstantDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Pseudo distribution, that has a unique constant value.
- ConstantDistribution(double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution
-
Constructor.
- ConstantDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Parameterization class
- ConstantWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions
-
Constant Weight function
The result is always 1.0
- ConstantWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ConstantWeight
-
- constantZero(List<V>, AttributeWiseCDFNormalization.Adapter) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization
-
Test if an attribute is constant zero.
- constraints - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.ListEachNumberConstraint
-
Constraints
- constraints - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter
-
Holds parameter constraints for this parameter.
- constraintValue - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.AbstractNumberConstraint
-
The constraint value.
- constructOneSignatures(SetDBIDs[][], long[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C
-
Construct the 1-signatures by merging adjacent dense bins.
- containedIn(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset
-
- containedIn(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Itemset
-
Test whether the itemset is contained in a bit vector.
- containedIn(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset
-
- containedIn(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset
-
- containedTest(IndexTreePath<E>, N, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Test on whether or not any child of node contains
mbr.
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate.COPACModel
-
- contains(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Returns true, if the intervals of this unit contain the specified feature
vector.
- contains(long[]) - Method in class de.lmu.ifi.dbs.elki.data.BitVector
-
Returns whether this BitVector contains all bits that are set to true in
the specified BitSet.
- contains(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
-
Returns true if the first SpatialComparable contains the second
SpatialComparable, false otherwise.
- contains(SpatialComparable, double[]) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
-
Returns true if this SpatialComparable contains the given point, false
otherwise.
- contains(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDs
-
Test whether an ID is contained.
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDArrayList
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNHeap
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDSubList
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.FastutilIntOpenHashSetModifiableDBIDs
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDKNNSubList
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerArrayDBIDs
-
- contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerDBIDs
-
- contains(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.KNNHeap
-
Check if an object is already in the heap.
- contains(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
-
- contains(O) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.Hierarchy
-
Check if an object is part of a hierarchy.
- contains(Class<?>) - Static method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry
-
Test if a registry entry has already been created.
- contains(String) - Method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClassManager
-
Check if a name is already used in the classes.
- containsIndex(int[], int) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Check if the index array contains i.
- containsKey(double) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerHeap
-
Contains operation for a key (slow: with a linear scan).
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap
-
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap
-
- containsKey(double) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongHeap
-
Contains operation for a key (slow: with a linear scan).
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap
-
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap
-
- containsKey(double) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectHeap
-
Contains operation for a key (slow: with a linear scan).
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap
-
- containsKey(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap
-
- containsKey(int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectHeap
-
Contains operation for a key (slow: with a linear scan).
- containsKey(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap
-
- containsKey(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap
-
- containsLeftNeighbor(CLIQUEUnit, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Returns true if this unit is the left neighbor of the given unit.
- containsPoint2D(double[]) - Method in class de.lmu.ifi.dbs.elki.data.spatial.Polygon
-
Point in polygon test, based on
http://www.ecse.rpi.edu/Homepages/wrf/Research/Short_Notes/pnpoly.html
by W.
- containsRightNeighbor(CLIQUEUnit, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Returns true if this unit is the right neighbor of the given unit.
- containsValue(int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerHeap
-
Contains operation for a value (slow: with a linear scan).
- containsValue(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap
-
- containsValue(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap
-
- containsValue(long) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongHeap
-
Contains operation for a value (slow: with a linear scan).
- containsValue(long) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap
-
- containsValue(long) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap
-
- containsValue(V) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectHeap
-
Contains operation for a value (slow: with a linear scan).
- containsValue(V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap
-
- containsValue(V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap
-
- containsValue(V) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectHeap
-
Contains operation for a value (slow: with a linear scan).
- containsValue(V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap
-
- containsValue(V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap
-
- content - Variable in class de.lmu.ifi.dbs.elki.database.relation.MaterializedDoubleRelation
-
Map to hold the objects of the database.
- content - Variable in class de.lmu.ifi.dbs.elki.database.relation.MaterializedRelation
-
Map to hold the objects of the database.
- contentChanged(DataStoreEvent) - Method in interface de.lmu.ifi.dbs.elki.database.datastore.DataStoreListener
-
Invoked after objects of the datastore have been updated, inserted or
removed in some way.
- contentChanged(DataStoreEvent) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
-
- contentChanged(DataStoreEvent) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext
-
Proxy datastore event to child listeners.
- contentChanged(DataStoreEvent) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisualization
-
- contents - Variable in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle
-
Storing the real contents.
- context - Variable in class de.lmu.ifi.dbs.elki.result.ExportVisualizations
-
Visualizer context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView
-
The visualizer context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot
-
Visualizer context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow
-
Visualizer context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
-
Our context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisualization
-
Our context
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction.SetStyleAction
-
Visualization context.
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.SwitchModeAction
-
Visualizer context.
- context - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.SwitchStyleAction
-
Visualizer context.
- contingency - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
-
Contingency matrix
- continueToMargin(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.CanvasSize
-
Continue a line along a given direction to the margin.
- contmat - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.ScoreResult
-
Cluster contingency table
- contrast - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.HiCSSubspace
-
The HiCS contrast value.
- controlsize - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance
-
Active area size
- convergence - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.AffinityPropagationClusteringAlgorithm
-
Terminate after 10 iterations with no changes.
- convergence - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.AffinityPropagationClusteringAlgorithm.Parameterizer
-
Number of stable iterations for convergence.
- CONVERGENCE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary
-
At which gene homogenity do we have convergence?
- convergence(int, int, boolean, boolean) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition
-
- CONVERGENCE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.AffinityPropagationClusteringAlgorithm.Parameterizer
-
Parameter for the convergence factor.
- convertedType(SimpleTypeInformation<I>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractConversionFilter
-
Get the output type from the input type after conversion.
- convertedType(SimpleTypeInformation<I>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamConversionFilter
-
Get the output type from the input type after conversion.
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.InverseDocumentFrequencyNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.HellingerHistogramNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.InstanceLogRankNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.InstanceMeanVarianceNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.InstanceMinMaxNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.InstanceRankNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.LengthNormalization
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.Log1PlusNormalization
-
- convertedType(SimpleTypeInformation<?>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.AbstractSupervisedProjectionVectorFilter
-
Get the output type from the input type after conversion.
- convertedType(SimpleTypeInformation<O>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.HistogramJitterFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.LatLngToECEFFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.LngLatToECEFFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.NumberVectorFeatureSelectionFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.NumberVectorRandomFeatureSelectionFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter
-
- convertedType(SimpleTypeInformation<I>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ProjectionFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.MultivariateTimeSeriesFilter
-
- convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.SparseVectorFieldFilter
-
- convertedType(SimpleTypeInformation<NumberVector>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.UncertainSplitFilter
-
- convertedType(SimpleTypeInformation<NumberVector>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.WeightedUncertainSplitFilter
-
- convertNeighbors(DBIDRange, DBIDRef, boolean, KNNList, DoubleArray, IntegerArray, Mean) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder
-
Load a neighbor query result into a double and and integer array, also
removing the query point.
- convertNeighbors(DBIDRange, DBIDRef, boolean, KNNList, DoubleArray, IntegerArray) - Method in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Load a neighbor query result into a double and and integer array, also
removing the query point.
- ConvertToBundleApplication - Class in de.lmu.ifi.dbs.elki.application
-
Convert an input file to the more efficient ELKI bundle format.
- ConvertToBundleApplication(DatabaseConnection, File) - Constructor for class de.lmu.ifi.dbs.elki.application.ConvertToBundleApplication
-
Constructor.
- ConvertToBundleApplication.Parameterizer - Class in de.lmu.ifi.dbs.elki.application
-
Parameterization class.
- convertToPointerRepresentation(ArrayDBIDs, DoubleLongHeap, WritableDBIDDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN
-
Convert spanning tree to a pointer representation.
- ConvertToStringView - Class in de.lmu.ifi.dbs.elki.database.relation
-
Representation adapter that uses toString() to produce a string
representation.
- ConvertToStringView(Relation<?>) - Constructor for class de.lmu.ifi.dbs.elki.database.relation.ConvertToStringView
-
Constructor.
- ConvexHull - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop
-
Holds the lower and upper hull for some values.
- ConvexHull(double[], double[]) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ConvexHull
-
Creates a new convex hull for the specified distances.
- Conviction - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest
-
Conviction interestingness measure:
\(\frac{P(X) P(\neg Y)}{P(X\cap\neg Y)}\).
- Conviction() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest.Conviction
-
Constructor.
- COORD - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
Pattern to catch coordinates
- coordinatesToHilbert(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter
-
Interleave one long per dimension (using the "bitsperdim" highest bits) to
a hilbert address.
- coordinatesToHilbert(int[], int, int) - Static method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter
-
Interleave one int per dimension (using the "bitsperdim" highest bits) to a
hilbert address.
- coordinatesToHilbert(short[], int, int) - Static method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter
-
Interleave one short per dimension (using the "bitsperdim" highest bits) to
a hilbert address.
- coordinatesToHilbert(byte[], int, int) - Static method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter
-
Interleave one byte per dimension (using the "bitsperdim" highest bits) to
a hilbert address.
- coordref - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea
-
The coordinate system node.
- coords - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
(Reused) storage of coordinates.
- COP<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier
-
Correlation outlier probability: Outlier Detection in Arbitrarily Oriented
Subspaces
Reference:
Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Outlier Detection in Arbitrarily Oriented Subspaces
Proc.
- COP(DistanceFunction<? super V>, int, PCARunner, double, COP.DistanceDist, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
-
Constructor.
- COP.DistanceDist - Enum in de.lmu.ifi.dbs.elki.algorithm.outlier
-
Score type.
- COP.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier
-
Parameterization class.
- COP_DIM - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
-
Result name for the dimensionality.
- COP_ERRORVEC - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
-
Result name for the error vectors.
- COP_SCORES - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
-
Result name for the COP outlier scores.
- COPAC<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
-
COPAC is an algorithm to partition a database according to the correlation
dimension of its objects and to then perform an arbitrary clustering
algorithm over the partitions.
- COPAC(COPAC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC
-
Constructor.
- COPAC.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
-
Parameterization class.
- COPAC.Settings - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
-
Class to wrap the COPAC settings.
- COPACModel(int, SetDBIDs) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate.COPACModel
-
COPAC model.
- COPACNeighborPredicate<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
COPAC neighborhood predicate.
- COPACNeighborPredicate(COPAC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate
-
Constructor.
- COPACNeighborPredicate.COPACModel - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Model used by COPAC for core point property.
- COPACNeighborPredicate.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Instance for a particular data set.
- COPACNeighborPredicate.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Parameterization class.
- COPOutlierScaling - Class in de.lmu.ifi.dbs.elki.utilities.scaling.outlier
-
CDF based outlier score scaling.
- COPOutlierScaling(double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.COPOutlierScaling
-
Constructor.
- COPOutlierScaling.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.scaling.outlier
-
Parameterization class.
- COPVectorVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier
-
Visualize error vectors as produced by COP.
- COPVectorVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier.COPVectorVisualization
-
Constructor.
- COPVectorVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier
-
Visualize error vectors as produced by COP.
- copy(double[]) - Static method in class de.lmu.ifi.dbs.elki.data.DoubleVector
-
Copy a double array into a new vector.
- copy(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Returns a copy of this vector.
- copy(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Make a deep copy of a matrix.
- copy(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Copy a bitset
- copy(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Copy a bitset.
- copy(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Copy a bitset.
- copyAttributes(Document, Element, Element) - Method in class de.lmu.ifi.dbs.elki.utilities.xml.DOMCloner
-
Copy the attributes from an existing node to a new node.
- copyFrom(SweepHullDelaunay2D.Triangle) - Method in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D.Triangle
-
Copy the values from another triangle.
- copyMeans(double[][], double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Instance
-
Copy means
- core - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util.Border
-
Cluster number
- Core - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util
-
Core point assignment.
- Core(int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util.Core
-
Constructor.
- core - Variable in class de.lmu.ifi.dbs.elki.data.model.CoreObjectsModel
-
Objects that are part of the cluster core.
- coredist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Instance
-
Core distances (if available, may be null).
- coredist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Instance
-
Core distances (if available, may be null).
- coredist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Instance
-
Core distances (if available, may be null).
- coreDistance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerDensityHierarchyRepresentationResult
-
Core distance.
- coredists - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HDBSCANAdapter
-
Core distance storage.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN
-
Track which objects are "core" objects.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance
-
Track which objects are "core" objects.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Track which objects are "core" objects.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN
-
Track which objects are "core" objects.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
Track which objects are "core" objects.
- coremodel - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Track which objects are "core" objects.
- COREMODEL_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Flag to keep track of core points.
- COREMODEL_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Flag to keep track of core points.
- CoreObjectsModel - Class in de.lmu.ifi.dbs.elki.data.model
-
Cluster model using "core" objects.
- CoreObjectsModel(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.data.model.CoreObjectsModel
-
Constructor.
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN
-
The core predicate factory.
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance
-
The core object property
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Core point predicate.
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN
-
The core predicate factory.
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
The core object property
- corepred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Core point predicate.
- COREPRED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Parameter for core predicate.
- COREPRED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Parameter for core predicate.
- CorePredicate<T> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Predicate for GeneralizedDBSCAN to evaluate whether a point is a core point
or not.
- CorePredicate.Instance<T> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Instance for a particular data set.
- cores - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
Core objects (shared)
- cores - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Core identifier objects (shared to conserve memory).
- CorrelationAnalysisSolution<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.data.model
-
A solution of correlation analysis is a matrix of equations describing the
dependencies.
- CorrelationAnalysisSolution(LinearEquationSystem, Relation<V>, double[][], double[][], double[][], double[]) - Constructor for class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
-
Provides a new CorrelationAnalysisSolution holding the specified matrix.
- CorrelationAnalysisSolution(LinearEquationSystem, Relation<V>, double[][], double[][], double[][], double[], NumberFormat) - Constructor for class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
-
Provides a new CorrelationAnalysisSolution holding the specified matrix and
number format.
- CorrelationClusterOrder - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics
-
Cluster order entry for correlation-based OPTICS variants.
- CorrelationClusterOrder(String, String, ArrayModifiableDBIDs, WritableDoubleDataStore, WritableDBIDDataStore, WritableIntegerDataStore) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.CorrelationClusterOrder
-
Constructor.
- CorrelationDependenceMeasure - Class in de.lmu.ifi.dbs.elki.math.statistics.dependence
-
Pearson product-moment correlation coefficient.
- CorrelationDependenceMeasure() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.dependence.CorrelationDependenceMeasure
-
- CorrelationDependenceMeasure.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.dependence
-
Parameterization class
- correlationDimensionality - Variable in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
-
The dimensionality of the correlation.
- correlationDistance(PCAFilteredResult, PCAFilteredResult, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO
-
Computes the correlation distance between the two subspaces defined by the
specified PCAs.
- CorrelationModel - Class in de.lmu.ifi.dbs.elki.data.model
-
Cluster model using a filtered PCA result and an centroid.
- CorrelationModel(PCAFilteredResult, double[]) - Constructor for class de.lmu.ifi.dbs.elki.data.model.CorrelationModel
-
Constructor
- correlationValue - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Instance
-
Correlation value.
- correlationValue - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.CorrelationClusterOrder
-
The correlation dimension.
- correlationValue - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance
-
Correlation value.
- correlationValue - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance
-
Correlation dimensionality.
- cos(int) - Method in class de.lmu.ifi.dbs.elki.math.SinCosTable
-
Get Cosine by step value.
- cos(int) - Method in class de.lmu.ifi.dbs.elki.math.SinCosTable.FullTable
-
Get Cosine by step value.
- cos(int) - Method in class de.lmu.ifi.dbs.elki.math.SinCosTable.HalfTable
-
Get Cosine by step value.
- cos(int) - Method in class de.lmu.ifi.dbs.elki.math.SinCosTable.QuarterTable
-
Get Cosine by step value.
- cosAngle(NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.data.VectorUtil
-
Compute the absolute cosine of the angle between two vectors.
- Cosine - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest
-
Cosine interestingness measure,
\(\tfrac{\text{support}(A\cup B)}{\sqrt{\text{support}(A)\text{support}(B)}}
=\tfrac{P(A\cap B)}{\sqrt{P(A)P(B)}}\).
- Cosine() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.associationrules.interest.Cosine
-
Constructor.
- CosineDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Cosine distance function for feature vectors.
- CosineDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.CosineDistanceFunction
-
- CosineDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Parameterization class.
- cosineFormulaDeg(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the approximate great-circle distance of two points using the
Haversine formula
Complexity: 6 trigonometric functions.
- cosineFormulaRad(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the approximate great-circle distance of two points using the
Spherical law of cosines.
- CosineHashFunctionFamily - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies
-
Hash function family to use with Cosine distance, using simplified hash
functions where the projection is only drawn from +-1, instead of Gaussian
distributions.
- CosineHashFunctionFamily(int, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.CosineHashFunctionFamily
-
Constructor.
- CosineHashFunctionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies
-
Parameterization class.
- CosineKernelDensityFunction - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions
-
Cosine kernel density estimator.
- CosineKernelDensityFunction() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.CosineKernelDensityFunction
-
Private, empty constructor.
- CosineKernelDensityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions
-
Parameterization stub.
- CosineKNNQuery(DistanceQuery<V>) - Constructor for class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex.CosineKNNQuery
-
Constructor.
- CosineLocalitySensitiveHashFunction - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfunctions
-
Random projection family to use with sparse vectors.
- CosineLocalitySensitiveHashFunction(RandomProjectionFamily.Projection) - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfunctions.CosineLocalitySensitiveHashFunction
-
Constructor.
- cosineOrHaversineDeg(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Use cosine or haversine dynamically.
- cosineOrHaversineRad(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Use cosine or haversine dynamically.
- CosineRangeQuery(DistanceQuery<V>) - Constructor for class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex.CosineRangeQuery
-
Constructor.
- CosineUnitlengthDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Cosine distance function for unit length feature vectors.
- CosineUnitlengthDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.CosineUnitlengthDistanceFunction
-
- CosineUnitlengthDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Parameterization class.
- cost - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARANS.Assignment
-
Array for storing the per-medoid costs.
- costable - Variable in class de.lmu.ifi.dbs.elki.math.SinCosTable.FullTable
-
Data store
- costable - Variable in class de.lmu.ifi.dbs.elki.math.SinCosTable.HalfTable
-
Data store
- costable - Variable in class de.lmu.ifi.dbs.elki.math.SinCosTable.QuarterTable
-
Data store
- cosZ - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.util.Simple1DOFCamera
-
Cache the Z rotation cosine
- count - Variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode
-
Key, weight, and number of children.
- count - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node
-
Number of elements
- count - Variable in class de.lmu.ifi.dbs.elki.datasource.DBIDRangeDatabaseConnection
-
Number of records to produce
- count - Variable in class de.lmu.ifi.dbs.elki.datasource.DBIDRangeDatabaseConnection.Parameterizer
-
Number of records to produce
- COUNT_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.DBIDRangeDatabaseConnection.Parameterizer
-
Parameter for number of IDs to generate
- countAboveThreshold(int[][], double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HSMDependenceMeasure
-
Count the number of cells above the threshold.
- countDistanceCalculation() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree.Statistics
-
Count a distance computation.
- countDistanceCalculation() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree.Statistics
-
Count a distance computation.
- countDistanceComputation() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree
-
Count a distance computation.
- countDistanceComputation() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree
-
Count a distance computation.
- counter - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.AtomicLongCounter
-
The counter to use.
- Counter - Interface in de.lmu.ifi.dbs.elki.logging.statistics
-
Simple statistic by counting.
- counter - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.UnsynchronizedLongCounter
-
The counter to use.
- counter - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
Counter, for max iterations of fast function.
- counter - Variable in class de.lmu.ifi.dbs.elki.result.ExportVisualizations
-
Output counter.
- counter - Static variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.ThumbnailRegistryEntry
-
Object counter
- countItemSupport(Relation<BitVector>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth
-
Count the support of each 1-item.
- countkNN(Object2IntOpenHashMap<Object>, Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.KNNEvaluator
-
Counting helper for kNN classification.
- countKNNQuery() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree.Statistics
-
Count a knn query invocation.
- countKNNQuery() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree.Statistics
-
Count a knn query invocation.
- countLeadingZeros(A, NumberArrayAdapter<?, ? super A>, int) - Static method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator
-
- countNonNewline(char[], int, int) - Method in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Count the number of non-newline characters before first newline in the string.
- countNonNewline(String, int, int) - Method in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Count the number of non-newline characters before first newline in the string.
- countObjectAccess() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree
-
Count a single object access.
- countObjectAccess() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree
-
Count a single object access.
- countRangeQuery() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree.Statistics
-
Count a range query invocation.
- countRangeQuery() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree.Statistics
-
Count a range query invocation.
- countRead() - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractPageFile
-
Count a page read access.
- countRefinement() - Method in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex
-
Count a single distance refinement.
- countRefinements(int) - Method in class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex
-
Increment the refinement counter, if in use.
- countSharedNeighbors(DBIDs, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.FractionalSharedNearestNeighborSimilarityFunction.Instance
-
Compute the intersection size.
- countSharedNeighbors(DBIDs, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.SharedNearestNeighborSimilarityFunction
-
Compute the intersection size
- CountSortAccesses(Counter, Relation<? extends NumberVector>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.CountSortAccesses
-
Constructor.
- countTies(double[], int[]) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
-
Count (and annotate) the number of tied values.
- countWrite() - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractPageFile
-
Count a page write access.
- covariance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel
-
Covariance matrix.
- covariance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.TextbookMultivariateGaussianModel
-
Covariance matrix.
- covariance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.TwoPassMultivariateGaussianModel
-
Covariance matrix.
- covarianceMatrix - Variable in class de.lmu.ifi.dbs.elki.data.model.EMModel
-
Cluster covariance matrix
- CovarianceMatrix - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
-
Class for computing covariance matrixes using stable mean and variance
computations.
- CovarianceMatrix(int) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix
-
Constructor.
- CovarianceMatrixBuilder - Interface in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
-
Interface for computing covariance matrixes on a data set.
- covarianceMatrixBuilder - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCARunner
-
The covariance computation class.
- covarianceMatrixBuilder - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCARunner.Parameterizer
-
The covariance computation class.
- coverage - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace
-
The coverage of this subspace, which is the number of all feature vectors
that fall inside the dense units of this subspace.
- coveringRadius - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeDirectoryEntry
-
The covering radius of the entry.
- coveringRadiusFromEntries(DBID, AbstractMTree<O, N, E, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode
-
Determines and returns the covering radius of this node.
- coverRadius(double[][], int[], int) - Static method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.MSTSplit
-
Find the cover radius of a partition.
- CoverTree<O> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
Cover tree data structure (in-memory).
- CoverTree(Relation<O>, DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree
-
Constructor.
- CoverTree.CoverTreeKNNQuery - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
KNN Query class.
- CoverTree.CoverTreeRangeQuery - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
Range query class.
- CoverTree.Factory<O> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
Index factory.
- CoverTree.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
Parameterization class.
- CoverTree.Node - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree
-
Node object.
- CoverTreeKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree.CoverTreeKNNQuery
-
Constructor.
- CoverTreeKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree.CoverTreeKNNQuery
-
Constructor.
- CoverTreeRangeQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree.CoverTreeRangeQuery
-
Constructor.
- CoverTreeRangeQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree.CoverTreeRangeQuery
-
Constructor.
- covmat - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform
-
Covariance matrix builder.
- covmat - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod
-
Working space for covariance matrix
- createBulkDirectoryNodes(List<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.NonFlatRStarTree
-
Creates and returns the directory nodes for bulk load.
- createBulkLeafNodes(List<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Creates and returns the leaf nodes for bulk load.
- createEmptyRoot(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree
-
Creates an empty root node and writes it to file.
- createEmptyRoot(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree
-
- createEmptyRoot(SpatialEntry) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
- createEmptyRoot(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.NonFlatRStarTree
-
- createHeader() - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree
-
Creates a header for this index structure which is an instance of
TreeIndexHeader.
- createHeader() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTreeUnified
-
- createHeader() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
- createImage(int, int) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.ThumbnailTranscoder
-
- createNewDirectoryEntry(N, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(MkAppTreeNode<O>, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(MkCoPTreeNode<O>, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(MkMaxTreeNode<O>, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree
-
- createNewDirectoryEntry(MkTabTreeNode<O>, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(MTreeNode<O>, DBID, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTree
-
- createNewDirectoryEntry(N) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(DeLiCluNode) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(FlatRStarTreeNode) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
- createNewDirectoryEntry(RdKNNNode) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
Creates a new directory entry representing the specified node.
- createNewDirectoryEntry(RStarTreeNode) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTree
-
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree
-
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTree
-
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
Creates a new directory node with the specified capacity.
- createNewDirectoryNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTree
-
Creates a new directory node with the specified capacity.
- createNewLeafEntry(DBID, O, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeIndex
-
Creates a new leaf entry representing the specified data object in the
specified subtree.
- createNewLeafEntry(DBID, O, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeIndex
-
Creates a new leaf entry representing the specified data object in the
specified subtree.
- createNewLeafEntry(DBID, O, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeIndex
-
- createNewLeafEntry(DBID, O, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeIndex
-
Creates a new leaf entry representing the specified data object in the
specified subtree.
- createNewLeafEntry(DBID, O, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex
-
- createNewLeafEntry(DBID) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeIndex
-
Creates a new leaf entry representing the specified data object.
- createNewLeafEntry(DBID) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeIndex
-
Wrap a vector as spatial point leaf entry.
- createNewLeafEntry(DBID) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
- createNewLeafEntry(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTreeIndex
-
Create a new leaf entry.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree
-
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree
-
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTree
-
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
Creates a new leaf node with the specified capacity.
- createNewLeafNode() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTree
-
Creates a new leaf node with the specified capacity.
- createNewRoot(N, N, DBID, DBID) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree
-
Creates a new root node that points to the two specified child nodes and
return the path to the new root.
- createNewRoot(N, N) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
-
Creates a new root node that points to the two specified child nodes and
return the path to the new root.
- createRoot(N, List<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.NonFlatRStarTree
-
Returns a root node for bulk load.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree
-
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTree
-
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTree
-
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
-
Creates an entry representing the root node.
- createRootEntry() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTree
-
- createScroller() - Method in class de.lmu.ifi.dbs.elki.gui.util.TreePopup
-
Creates the scroll pane which houses the scrollable tree.
- createSettings() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeFactory.Parameterizer
-
Create the settings object
- createSettings() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeFactory.Parameterizer
-
- createSettings() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeFactory.Parameterizer
-
- createSettings() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTreeFactory.Parameterizer
-
- createSettings() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTreeFactory.Parameterizer
-
- createStorage() - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor
-
Create the default storage.
- createTree() - Method in class de.lmu.ifi.dbs.elki.gui.util.TreePopup
-
Creates the JList used in the popup to display the items in the combo box
model.
- createVector() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Creates a database object of type V.
- cref - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.JSVGUpdateSynchronizer
-
A weak reference to the component the plot is in.
- crep - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
-
Class label representation
- crossoverOptimized(ArrayList<AggarwalYuEvolutionary.Individuum>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch
-
method implements the crossover algorithm
- crossTrackDistanceDeg(double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the cross-track distance.
- crossTrackDistanceDeg(double, double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the cross-track distance.
- crossTrackDistanceRad(double, double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the cross-track distance.
- crossTrackDistanceRad(double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
-
Compute the cross-track distance.
- cs - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util.MultiBorder
-
Cluster numbers
- csize - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationBuilder
-
Cluster size storage.
- CSS_ARROW - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance
-
CSS tag for our event rectangle
- CSS_AXIS - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGSimpleLinearAxis
-
CSS class name for the axes
- CSS_AXIS_LABEL - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGSimpleLinearAxis
-
CSS class name for the axes
- CSS_AXIS_LABEL - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYCurveVisualization
-
Axis labels
- CSS_AXIS_LABEL - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYPlotVisualization
-
Axis labels
- CSS_AXIS_TICK - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGSimpleLinearAxis
-
CSS class name for the axes
- CSS_BRACKET - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization.Instance
-
CSS class for markers
- CSS_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainBoundingBoxVisualization.Instance
-
CSS class for uncertain bounding boxes.
- CSS_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainInstancesVisualization.Instance
-
CSS class for uncertain bounding boxes.
- CSS_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization.Instance
-
CSS class for uncertain bounding boxes.
- CSS_CUBE - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Instance
-
CSS class for the filled cube
- CSS_CUBEFRAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Instance
-
CSS class for the cube frame
- CSS_EPSILON - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
-
CSS-Styles
- CSS_LINE - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
-
CSS-Styles
- CSS_MARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance
-
CSS class for markers
- CSS_MEAN - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterMeanVisualization.Instance
-
CSS class name for center of the means
- CSS_MEAN_CENTER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterMeanVisualization.Instance
-
CSS class name for center of the means
- CSS_MEAN_STAR - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterStarVisualization.Instance
-
CSS class name for center of the means
- CSS_RANGEMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance
-
CSS class for markers
- CSS_RANGEMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance
-
Generic tag to indicate the type of element.
- CSS_RANGEMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance
-
CSS class of the selection rectangle while selecting.
- CSS_RANGEMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance
-
Generic tag to indicate the type of element.
- CSS_RANGEMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance
-
CSS class of the selection rectangle while selecting.
- CSS_STEEP_DOWN - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization.Instance
-
CSS class for markers
- CSS_STEEP_UP - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization.Instance
-
CSS class for markers
- cssclass - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.AddCSSClass
-
Class to set
- cssclass - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.RemoveCSSClass
-
Class to set
- CSSClass - Class in de.lmu.ifi.dbs.elki.visualization.css
-
Class representing a single CSS class.
- CSSClass(Object, String, Collection<Pair<String, String>>) - Constructor for class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Full constructor
- CSSClass(Object, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Simplified constructor, empty statements list.
- CSSClass(Object, String, CSSClass) - Constructor for class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
Cloning constructor
- CSSClass.InvalidCSS - Exception in de.lmu.ifi.dbs.elki.visualization.css
-
Exception class thrown when encountering invalid CSS.
- CSSClassManager - Class in de.lmu.ifi.dbs.elki.visualization.css
-
Manager class to track CSS classes used in a particular SVG document.
- CSSClassManager() - Constructor for class de.lmu.ifi.dbs.elki.visualization.css.CSSClassManager
-
- CSSClassManager.CSSNamingConflict - Exception in de.lmu.ifi.dbs.elki.visualization.css
-
Class to signal a CSS naming conflict.
- CSSHoverClass - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
Do a hover effect using a CSS class.
- CSSHoverClass(String, String, boolean) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.CSSHoverClass
-
Constructor
- CSSHoverClass(String, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.CSSHoverClass
-
Constructor without 'clickisout' option.
- cssman - Variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot
-
CSS class manager
- CSSNAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterOrderVisualization.Instance
-
CSS class name
- CSSNamingConflict(String) - Constructor for exception de.lmu.ifi.dbs.elki.visualization.css.CSSClassManager.CSSNamingConflict
-
Exception to signal a CSS naming conflict.
- CSVReaderFormat - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Basic format factory for parsing CSV-like formats.
- CSVReaderFormat(Pattern, String, Pattern) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat
-
Constructor.
- CSVReaderFormat.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Parameterization class.
- CTLuGLSBackwardSearchAlgorithm<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
GLS-Backward Search is a statistical approach to detecting spatial outliers.
- CTLuGLSBackwardSearchAlgorithm(DistanceFunction<? super V>, int, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm
-
Constructor.
- CTLuGLSBackwardSearchAlgorithm.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class
- CTLuMeanMultipleAttributes<N,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Mean Approach is used to discover spatial outliers with multiple attributes.
- CTLuMeanMultipleAttributes(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuMeanMultipleAttributes
-
Constructor
- CTLuMeanMultipleAttributes.Parameterizer<N,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuMedianAlgorithm<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Median Algorithm of C.
- CTLuMedianAlgorithm(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuMedianAlgorithm
-
Constructor.
- CTLuMedianAlgorithm.Parameterizer<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuMedianMultipleAttributes<N,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Median Approach is used to discover spatial outliers with multiple
attributes.
- CTLuMedianMultipleAttributes(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuMedianMultipleAttributes
-
Constructor
- CTLuMedianMultipleAttributes.Parameterizer<N,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuMoranScatterplotOutlier<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Moran scatterplot outliers, based on the standardized deviation from the
local and global means.
- CTLuMoranScatterplotOutlier(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuMoranScatterplotOutlier
-
Constructor.
- CTLuMoranScatterplotOutlier.Parameterizer<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuRandomWalkEC<P> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Spatial outlier detection based on random walks.
- CTLuRandomWalkEC(DistanceFunction<? super P>, double, double, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC
-
Constructor.
- CTLuRandomWalkEC.Parameterizer<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuScatterplotOutlier<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Scatterplot-outlier is a spatial outlier detection method that performs a
linear regression of object attributes and their neighbors average value.
- CTLuScatterplotOutlier(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuScatterplotOutlier
-
Constructor.
- CTLuScatterplotOutlier.Parameterizer<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- CTLuZTestOutlier<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Detect outliers by comparing their attribute value to the mean and standard
deviation of their neighborhood.
- CTLuZTestOutlier(NeighborSetPredicate.Factory<N>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuZTestOutlier
-
Constructor.
- CTLuZTestOutlier.Parameterizer<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
-
Parameterization class.
- ctrlLayer - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
The two main layers
- cubicTo(double, double, double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
-
Cubic Bezier line to the given coordinates.
- cubicTo(double[], double[], double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
-
Cubic Bezier line to the given coordinates.
- cur - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepScanPosition
-
Variable for accessing.
- cur - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.IterableIt
-
Current object.
- cur - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.overview.PlotItem.ItmItr
-
- curclu - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
Current clustering.
- curclus - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain.AssignLabelsByDensity
-
Current cluster generator.
- cureid - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
Current external id.
- curid - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.FixedDBIDsFilter
-
The next ID to assign
- curlbl - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
Current labels.
- curlbl - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Current labels.
- curlbl - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
Current labels.
- curpoly - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
Current polygon.
- current - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree.LeafIterator
-
Current leaf entry.
- current - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
Current value
- current - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.FilteredIt
-
Current object, if valid.
- current - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.SubtypeIt
-
Current object, if valid.
- current - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.MergedParameterization
-
Parameters we used before, but have rewound
- currentCluster(List<? extends ModifiableDBIDs>, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPark
-
Find the current cluster assignment.
- currentDataStoreEventType - Variable in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager
-
The type of the current DataStoreEvent to be accumulated.
- currentSubplot - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow
-
Currently selected subplot.
- Curve(int) - Constructor for class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve
-
Constructor.
- Curve(int, int) - Constructor for class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve
-
Constructor.
- curvec - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Current vector.
- curvec - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
-
Current vector.
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor
-
Spatial curve generators
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.Factory
-
Spatial curve generators
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.Factory.Parameterizer
-
Spatial curve generators.
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor
-
Spatial curve generators
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor.Factory
-
Spatial curve generators
- curvegen - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer
-
Spatial curve generators
- curves - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor
-
Curve storage
- curves - Variable in class de.lmu.ifi.dbs.elki.math.geometry.XYPlot
-
Curves on this plot.
- curves - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.ColoredHistogramVisualizer.Parameterizer
-
Internal storage of the curves flag.
- CURVES_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.Factory.Parameterizer
-
Parameter for choosing the space filling curves to use.
- CURVES_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer
-
Parameter for choosing the space filling curves to use.
- cusum(double[], double[], int, int) - Static method in class de.lmu.ifi.dbs.elki.algorithm.timeseries.OfflineChangePointDetectionAlgorithm
-
Compute the incremental sum of an array, i.e. the sum of all points up to
the given index.
- CutDendrogramByHeight - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
-
Extract a flat clustering from a full hierarchy, represented in pointer form.
- CutDendrogramByHeight(HierarchicalClusteringAlgorithm, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.CutDendrogramByHeight
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Constructor.
- CutDendrogramByHeight.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
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Instance for a single data set.
- CutDendrogramByHeight.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
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Parameterization class.
- CutDendrogramByHeightExtractor - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
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Extract clusters from a hierarchical clustering, during the evaluation phase.
- CutDendrogramByHeightExtractor(CutDendrogramByHeight) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.CutDendrogramByHeightExtractor
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Constructor.
- CutDendrogramByHeightExtractor.DummyHierarchicalClusteringAlgorithm - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
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Dummy instance.
- CutDendrogramByHeightExtractor.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
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Parameterization class.
- CutDendrogramByNumberOfClusters - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
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Extract a flat clustering from a full hierarchy, represented in pointer form.
- CutDendrogramByNumberOfClusters(HierarchicalClusteringAlgorithm, int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.CutDendrogramByNumberOfClusters
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Constructor.
- CutDendrogramByNumberOfClusters.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
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Instance for a single data set.
- CutDendrogramByNumberOfClusters.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
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Parameterization class.
- CutDendrogramByNumberOfClustersExtractor - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
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Extract clusters from a hierarchical clustering, during the evaluation phase.
- CutDendrogramByNumberOfClustersExtractor(CutDendrogramByNumberOfClusters) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.CutDendrogramByNumberOfClustersExtractor
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Constructor.
- CutDendrogramByNumberOfClustersExtractor.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
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Parameterization class.
- CUTOFF - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS
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Significance cutoff when computing kernel density.
- cutoff - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS
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Candidates limit.
- cutoff - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.Parameterizer
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- cutoff - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.TopKOutlierScaling
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The value we cut off at.
- cycleLeftC(long, int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
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Rotate a long to the left, cyclic with length len
- cycleLeftI(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
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Cycle a bitstring to the right.
- cycleRightC(long, int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
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Rotate a long to the right, cyclic with length len
- cycleRightI(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
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Cycle a bitstring to the right.
