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C

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.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
 
C2 - 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.GeneralizedExtremeValueLMMEstimator
 
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.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction
The distance matrix
cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction.Parameterizer
 
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
 
cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedDoubleDistanceFunction
The distance cache
cache - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedFloatDistanceFunction
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.
cachec - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatDynamicHistogram
Cache for data to be inserted.
cachec - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntDynamicHistogram
Cache for data to be inserted.
cachec - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongDynamicHistogram
Cache for data to be inserted.
cachec - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortDynamicHistogram
Cache for data to be inserted.
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(InputStep, DistanceFunction<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(InputStep, DistanceFunction<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(InputStep, DistanceFunction<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
cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatDynamicHistogram
Cache fill size
cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntDynamicHistogram
Cache fill size
cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongDynamicHistogram
Cache fill size
cachefill - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortDynamicHistogram
Cache fill size
CacheFloatDistanceInOnDiskMatrix<O> - Class in de.lmu.ifi.dbs.elki.application.cache
Precompute an on-disk distance matrix, using float precision.
CacheFloatDistanceInOnDiskMatrix(InputStep, DistanceFunction<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.
cachev - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatDynamicHistogram
Cache for data to be inserted.
cachev - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntDynamicHistogram
Cache for data to be inserted.
cachev - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongDynamicHistogram
Cache for data to be inserted.
cachev - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortDynamicHistogram
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.MixtureModelOutlierScalingFunction
Compute p_i (Gaussian distribution, outliers)
calcPosterior(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScalingFunction
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.MixtureModelOutlierScalingFunction
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.
calculateContrast(Relation<? extends NumberVector>, DBIDs, ArrayDBIDs, ArrayDBIDs, int, int, Random) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HiCSDimensionSimilarity
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
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(Matrix, double, int) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner.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, String) - 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
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(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.BitsUtil
Compute the cardinality (number of set bits)
cardinality(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.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!).
castWithGenericsOrNull(Class<B>, Object) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
Cast an object at a base class, but return a subclass (for Generics!).
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.math.linearalgebra.randomprojections
Random projections using Cauchy distributions (1-stable).
CauchyRandomProjectionFamily(RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.CauchyRandomProjectionFamily
Constructor.
CauchyRandomProjectionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections
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.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, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedExtremeValueDistribution
CDF of GEV distribution
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.GeneralizedLogisticAlternateDistribution
Cumulative density function.
cdf(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticAlternateDistribution
 
cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticDistribution
Cumulative density function.
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.GeneralizedParetoDistribution
CDF of GEV 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 Weibull 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, 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.LogGammaAlternateDistribution
 
cdf(double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogGammaAlternateDistribution
The CDF, 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, 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.LogisticDistribution
 
cdf(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.LogLogisticDistribution
 
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) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.WaldDistribution
 
cdf(double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.WaldDistribution
Cumulative probability density function (CDF) of a Wald distribution.
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.
cdiv(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
 
cdivi - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
 
cdivr - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
 
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 - 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(Matrix) - 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.
centroid - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.ORCLUSCluster
The centroid of this cluster.
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 - Variable in class de.lmu.ifi.dbs.elki.data.model.CorrelationModel
The centroid of this cluster.
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.
CentroidLinkageMethod - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
Centroid linkage clustering method, aka UPGMC: Unweighted Pair-Group Method using Centroids.
CentroidLinkageMethod() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CentroidLinkageMethod
Deprecated.
use the static instance CentroidLinkageMethod.STATIC instead.
CentroidLinkageMethod.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
Class parameterizer.
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.
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.
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.
cheatToAvoidSingularity(double) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Adds a given value to the diagonal entries if the entry is smaller than the constant.
checkAliases(Class<?>, String, String[]) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckELKIServices
Check if aliases are listed completely.
checkClusters(Relation<V>, TCustomHashMap<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.
checkConstraint(GlobalParameterConstraint) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.AbstractParameterization
 
checkConstraint(GlobalParameterConstraint) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.MergedParameterization
 
checkConstraint(GlobalParameterConstraint) - Method in interface de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization
Check a parameter constraint.
checkConstraint(GlobalParameterConstraint) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.TrackParameters
 
checkConstraint(GlobalParameterConstraint) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.UnParameterization
 
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.
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
 
checkHeap() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap
Test whether the heap is still valid.
checkMatrixDimensions(Matrix) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Check if size(A) == size(B)
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
 
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.
checkV1Parameterization(Class<?>, CheckParameterizables.State) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
Check for a V1 constructor.
checkV2Parameterization(Class<?>, CheckParameterizables.State) - Method in class de.lmu.ifi.dbs.elki.application.internal.CheckParameterizables
Check for a V2 constructor.
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
Perform 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.
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.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.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
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
Chi-Squared distance function, symmetric version.
ChiSquaredDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiSquaredDistanceFunction
Deprecated.
Use static instance!
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: Algorithm AS 91: The percentage points of the $\chi^2$ distribution
D.J.
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.
CholeskyDecomposition - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
Cholesky Decomposition.
CholeskyDecomposition(Matrix) - 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<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestPointsInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestSumPointsInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FirstKInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<O>) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansInitialization
Choose initial means
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.KMeansPlusPlusInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PAMInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.PredefinedInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomlyChosenInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.RandomlyGeneratedInitialMeans
 
chooseInitialMeans(Database, Relation<T>, int, NumberVectorDistanceFunction<? super T>, NumberVector.Factory<O>) - 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.PAMInitialMeans
 
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<O, N, E, ?>, E) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert.MinimumEnlargementInsert
 
choosePath(AbstractMTree<O, 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<O, 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.
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<? super NumberVector>) - 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, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA
Constructor.
CLARA.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
Deprecated.
Use ClarkDistanceFunction.STATIC instance instead.
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
Utils for handling class instantiation especially with respect to Java generics.
ClassGenericsUtil() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
Fake Constructor.
ClassicMultidimensionalScalingTransform<O> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
Rescale the data set using multidimensional scaling, MDS.
ClassicMultidimensionalScalingTransform(int, PrimitiveDistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform
Constructor.
ClassicMultidimensionalScalingTransform.Parameterizer<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
 
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.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.
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
 
ClassSorter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.ClassSorter
 
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
 
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.
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.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.database.datastore.memory.ArrayDoubleStore
 
clear() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDoubleStore
 
clear() - Method in interface de.lmu.ifi.dbs.elki.database.datastore.WritableDoubleDataStore
Reinitialize (reset to 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.DoubleIntegerDBIDKNNHeap
 
clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList
 
clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap
 
clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList
 
clear() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TroveHashSetModifiableDBIDs
 
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() - 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.hash.Unique
 
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.
clearC(long, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.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
 
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.
CLIQUE<V extends NumberVector> - 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<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace
Parameterization class.
CLIQUEInterval - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique
Represents an interval in a certain dimension of the data space.
CLIQUEInterval(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEInterval
Creates a new interval with the specified parameters.
CLIQUESubspace<V extends NumberVector> - 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.
CLIQUESubspace.CoverageComparator - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique
A partial comparator for CLIQUESubspaces based on their coverage.
CLIQUEUnit<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique
Represents a unit in the CLIQUE algorithm.
CLIQUEUnit(ArrayList<CLIQUEInterval>, 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(CLIQUEInterval) - 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
clone() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation
Return a clone of the affine transformation
clone() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Clone the Matrix object.
clone() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
 
cloneBits() - Method in class de.lmu.ifi.dbs.elki.data.BitVector
Returns a copy of the bits currently set in this BitVector.
cloneCollection(C) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
Clone a collection.
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
 
cloneNode(Document, Node) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot.CloneNoExport
 
CloneNoExport() - Constructor for class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot.CloneNoExport
 
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.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.
closeArray() - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer
Close an array context.
closeButton - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
Button to close the window
closeHash() - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer
Close an hash context.
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.
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.
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
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.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 - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
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_EMPTY - Static variable in interface de.lmu.ifi.dbs.elki.utilities.exceptions.ExceptionMessages
Message when an empty clustering is encountered.
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
Constructor - use the static instance ClusteringAdjustedRandIndexSimilarityFunction.STATIC!
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.
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
 
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
Constructor - use the static instance ClusteringBCubedF1SimilarityFunction.STATIC!
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.
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
Constructor - use the static instance ClusteringFowlkesMallowsSimilarityFunction.STATIC!
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
Constructor - use the static instance ClusteringRandIndexSimilarityFunction.STATIC!
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
Class to 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
Parser for simple clustering results in vector form, as written by ClusteringVectorDumper.
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
Constructor - use the static instance ClusterIntersectionSimilarityFunction.STATIC!
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
Constructor - use the static instance ClusterJaccardSimilarityFunction.STATIC!
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.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
Action to use a clustering as ClusterStylingPolicy.
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.
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.
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.
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(Clustering<DendrogramModel>, HDBSCANHierarchyExtraction.TempCluster, Cluster<DendrogramModel>, boolean, boolean) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster
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
collectionToArray(Collection<T>, T[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil
Transform a collection to an Array
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.geo.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.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
cols - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleArrayStaticHistogram
Desired number of columns in each bin.
cols - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntArrayStaticHistogram
Desired number of columns in each bin.
cols - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongArrayStaticHistogram
Desired number of columns in each bin.
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.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
OptionID for the column separator parameter (defaults to whitespace as in CSVReaderFormat.DEFAULT_SEPARATOR.
columndimension - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Column dimension.
columnnames - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
Column names.
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.CentroidLinkageMethod
 
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CompleteLinkageMethod
 
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.GroupAverageLinkageMethod
 
combine(int, double, int, double, int, double) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.LinkageMethod
Compute combined linkage for two clusters.
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.MedianLinkageMethod
 
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.SingleLinkageMethod
 
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.WardLinkageMethod
 
combine(int, double, int, double, int, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.WeightedAverageLinkageMethod
 
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, 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.
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(TIntArrayList, 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
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
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.
ComparableMaxHeap<K extends 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 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 - Static variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
Comparator for sorting the list of classes for each reference.
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 or null.
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.correlation.HiCO.Instance.Sorter
 
compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.GeneralizedOPTICS.Instance
 
compare(CLIQUESubspace<?>, CLIQUESubspace<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace.CoverageComparator
Compares the two specified CLIQUESubspaces for order.
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(OptionID, OptionID) - Method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters.SortByOption
 
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(Subspace, Subspace) - Method in class de.lmu.ifi.dbs.elki.data.Subspace.DimensionComparator
Compares the two specified subspaces for order.
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.DescendingByDoubleDataStore
 
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(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.result.OrderingFromDataStore.DerivedComparator
 
compare(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.result.OrderingFromDataStore.ImpliedComparator
 
compare(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Compare two bitsets.
compare(int, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.arrays.IntegerComparator
Compare two Integer.
compare(Object, Object) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.TopBoundedUpdatableHeap
Test if the priority of an object is higher.
compare(Class<?>, Class<?>) - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.ClassSorter
 
compare(Comparable<Object>, Comparable<Object>) - Method in class de.lmu.ifi.dbs.elki.utilities.Util.ForwardComparator
 
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.
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
Compares this object with the specified object for order.
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(DeLiClu<NV>.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(CLIQUEInterval) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEInterval
Compares this interval with the specified interval for order.
compareTo(PROCLUS.DoubleIntInt) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.DoubleIntInt
 
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.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
The ordering of two SimpleClassLabels is given by the ordering on the Strings they represent.
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(DistanceEntry<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.DistanceEntry
Compares this object with the specified object for order.
compareTo(DoubleDistanceSearchCandidate) - Method in class de.lmu.ifi.dbs.elki.index.tree.query.DoubleDistanceSearchCandidate
 
compareTo(GenericMTreeDistanceSearchCandidate) - Method in class de.lmu.ifi.dbs.elki.index.tree.query.GenericMTreeDistanceSearchCandidate
 
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.EigenPair
Compares this object with the specified object for order.
compareTo(HilbertSpatialSorter.HilbertRef<T>) - Method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter.HilbertRef
 
compareTo(DoublePriorityObject<?>) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoublePriorityObject
 
compareTo(IntegerPriorityObject<?>) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerPriorityObject
 
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.visualization.batikutil.ThumbnailRegistryEntry.InternalParsedURLData
 
completeBasis() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Completes this d x c basis of a subspace of R^d to a d x d basis of R^d, i.e. appends c-d columns to this basis.
completed - Variable in class de.lmu.ifi.dbs.elki.logging.progress.IndefiniteProgress
Store completion flag.
CompleteLinkageMethod - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
Complete-linkage clustering method.
CompleteLinkageMethod() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.CompleteLinkageMethod
Deprecated.
use the static instance CompleteLinkageMethod.STATIC instead.
CompleteLinkageMethod.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
Class parameterizer.
completeToOrthonormalBasis() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Completes this d x c basis of a subspace of R^d to a d x d basis of R^d, i.e. appends c-d columns to this basis.
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.
CompositeEigenPairFilter - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
The CompositeEigenPairFilter can be used to build a chain of eigenpair filters.
CompositeEigenPairFilter(List<EigenPairFilter>) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CompositeEigenPairFilter
Constructor.
CompositeEigenPairFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
Parameterization class.
compute() - Method in class de.lmu.ifi.dbs.elki.math.geometry.AlphaShape
 
computeABOF(Relation<V>, KernelMatrix, DBIDRef, MeanVariance) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD
Compute the exact ABOF value.
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.RandomProjectedNeighborssAndDensities
Compute for each point a density estimate as inverse of average distance to a point in a projected set
computeBadMedoids(ArrayDBIDs, ArrayList<PROCLUS<V>.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.
computeCentroids(int, List<V>, List<ClassLabel>, Map<ClassLabel, TIntList>) - 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.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.
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<V>>, 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.
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.CovarianceDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends V>, DBIDs, DimensionSimilarityMatrix) - Method in interface de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarity
Compute the dimension similarity matrix
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HiCSDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HSMDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.MCEDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.SlopeDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.SlopeInversionDimensionSimilarity
 
computeDimensionSimilarites(Relation<? extends NumberVector>, DBIDs, DimensionSimilarityMatrix) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.SURFINGDimensionSimilarity
 
computeDistanceMatrix(List<O>, int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform
 
computeDistanceMatrix(List<O>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.FastMultidimensionalScalingTransform
Compute the distance matrix of a vector column.
computeDistanceMatrix(AbstractMTree<O, N, E, ?>, N) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.MTreeSplit
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(FilteredEigenPairs) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner
Compute the explained variance for a FilteredEigenPairs.
computeFirstCover(boolean) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.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.
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.
computeIncreaseArea(double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.RectangleArranger
 
computeINFLO(Relation<O>, ModifiableDBIDs, WritableDataStore<ModifiableDBIDs>, WritableDataStore<ModifiableDBIDs>, WritableDoubleDataStore, 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>, int, int, int, ByLabelOutlier, File, ScalingFunction, Pattern) - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores
Constructor.
ComputeKNNOutlierScores.AlgRunner - Interface in de.lmu.ifi.dbs.elki.application.greedyensemble
Run an algorithm for a given k.
ComputeKNNOutlierScores.Parameterizer<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.application.greedyensemble
Parameterization class.
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[], double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator
Compute the median absolute deviation from median.
computeMAD(double[], double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator
Compute the median absolute deviation from median.
computeMAD(double[], double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator
Compute the median absolute deviation from median.
computeMAD(double[], double, double[], int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.BestFitEstimator
 
computeMBR() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode
Recomputing the MBR is rather expensive.
computeMeans(List<CLIQUESubspace<V>>) - 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.
computeMedoid(Relation<? extends NumberVector>, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.data.VectorUtil
Compute medoid for a given subset.
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(List<? extends SpatialComparable>) - Static method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.AbstractSpatialSorter
Compute the minimum and maximum for each dimension.
computeNeighborhoods(Relation<O>, KNNQuery<O>, ModifiableDBIDs, WritableDataStore<ModifiableDBIDs>, WritableDataStore<ModifiableDBIDs>, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.INFLO
Compute neighborhoods
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.histogram
Compute a Histogram to evaluate a ranking algorithm.
ComputeOutlierHistogram(Pattern, int, ScalingFunction, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.histogram.ComputeOutlierHistogram
Constructor.
ComputeOutlierHistogram.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.histogram
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>, Vector, 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.
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
 
computePrecisionResult(int, SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierPrecisionAtKCurve
 
computePrecisionResult(int, 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
 
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.
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(int, SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierROCCurve
 
computeROCResult(int, 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.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.RandomProjectedNeighborssAndDensities
Create random projections, project points and put points into sets of size about minSplitSize/2
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.
computeSmROCResult(SetDBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierSmROCCurve
 
computeStopDistance(List<KNNHeap>) - Method in class de.lmu.ifi.dbs.elki.algorithm.KNNJoin
Compute the maximum stop distance.
computeSubspace(ArrayList<IntIntPair>, 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.
computeTau(long, long, double, long, long) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
Compute the Tau correlation measure
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
computeWithinDistances(Relation<? extends NumberVector>, List<? extends Cluster<?>>, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
 
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.
cond() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Matrix condition (2 norm)
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
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.clustering.correlation.ORCLUS.Parameterizer
 
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.ERiC.Settings.Parameterizer
Configure the delta parameter.
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.COPAC.Settings.Parameterizer
Configure the epsilon radius 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
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.clustering.AbstractProjectedClustering.Parameterizer
configK(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC.Settings.Parameterizer
Configure the kNN parameter.
configK(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings.Parameterizer
Configure the kNN 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.
configKI(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering.Parameterizer
configL(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering.Parameterizer
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.COPAC.Settings.Parameterizer
Configure the minPts aka "mu" parameter.
configMinPts(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings.Parameterizer
Configure the minPts aka "mu" 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
configSeed(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.Parameterizer
 
configTau(Parameterization) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings.Parameterizer
Configure the tau 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.
cons - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.ParameterFlagGlobalConstraint
List of parameter constraints.
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.ListEachConstraint
Constraints
constraints - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter
Holds parameter constraints for this parameter.
constraintStrings() - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.EqualStringConstraint
 
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.
constructWithCopy(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Construct a matrix from a copy of a 2-D array.
containedIn(BitVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset
 
containedIn(BitVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Itemset
Test whether the itemset is contained in a bit vector.
containedIn(BitVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset
 
containedIn(BitVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset
 
containedIn(BitVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SparseItemset
 
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(V) - 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.generic.KNNSubList
 
contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.MaskedDBIDs
 
contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableArrayDBIDs
 
contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableDBIDs
 
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.DoubleIntegerDBIDList
 
contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap
 
contains(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList
 
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.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.TroveHashSetModifiableDBIDs
 
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(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.
containsKey(int, int) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.external.DistanceCacheWriter
Returns true if the specified distance cache contains a distance value for the specified ids.
containsLeftNeighbor(CLIQUEInterval) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
Returns true if this unit contains the left neighbor of the specified interval.
containsPoint2D(Vector) - 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(CLIQUEInterval) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
Returns true if this unit contains the right neighbor of the specified interval.
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.
CONTENT_TYPE_CSS - Static variable in class de.lmu.ifi.dbs.elki.utilities.xml.HTMLUtil
CSS content type
CONTENT_TYPE_HTML - Static variable in class de.lmu.ifi.dbs.elki.utilities.xml.HTMLUtil
HTML content type
CONTENT_TYPE_HTML_UTF8 - Static variable in class de.lmu.ifi.dbs.elki.utilities.xml.HTMLUtil
HTML content type with UTF-8 indication
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.visualization.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.VisualizationTask
The active 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.
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_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.AbstractNormalization
 
convertedType(SimpleTypeInformation<V>) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.AbstractStreamNormalization
 
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
 
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.
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 Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Outlier Detection in Arbitrarily Oriented Subspaces
in: 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.
COPAC.Settings.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Parameterization class.
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() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Make a deep copy of a matrix.
copy() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs
Returns a deep copy of this object
copy() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Returns a copy of this 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.BitsUtil
Copy a bitset
copy(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Copy a bitset.
copy(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.
copyToFullMatrix() - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix
Transform linear triangle matrix into a full matrix.
core - Variable in class de.lmu.ifi.dbs.elki.data.model.CoreObjectsModel
Objects that are part of the cluster core.
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_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.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_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
Parameter for core predicate.
CorePredicate - 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.
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>, Matrix, Matrix, Matrix, Vector) - Constructor for class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
Provides a new CorrelationAnalysisSolution holding the specified matrix.
CorrelationAnalysisSolution(LinearEquationSystem, Relation<V>, Matrix, Matrix, Matrix, Vector, 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
Constructor - use CorrelationDependenceMeasure.STATIC instance.
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<V extends FeatureVector<?>> - Class in de.lmu.ifi.dbs.elki.data.model
Cluster model using a filtered PCA result and an centroid.
CorrelationModel(PCAFilteredResult, V) - 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.
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
Deprecated.
Use static instance
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 (2 of which emulated) 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.
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.
CosineRangeQuery(DistanceQuery<V>) - Constructor for class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex.CosineRangeQuery
Constructor.
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
cosToSin(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
Fast way of computing sin(x) from x and cos(x).
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.dimensionsimilarity.HSMDimensionSimilarity
Count the number of cells above the threshold.
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 - Static variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.ThumbnailRegistryEntry
Object counter
counter - Variable in class de.lmu.ifi.dbs.elki.visualization.ExportVisualizations
Output counter
countItemSupport(Relation<BitVector>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth
Count the support of each 1-item.
countkNN(TObjectIntHashMap<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.
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.
countStrongEigenPairs() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.FilteredEigenPairs
Counts the strong eigenpairs.
countTies(double[], int[]) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
Count (and annotate) the number of tied values.
countWeakEigenPairs() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.FilteredEigenPairs
Counts the strong eigenpairs.
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, and inverse.
CovarianceDimensionSimilarity - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity
Class to compute the dimension similarity based on covariances.
CovarianceDimensionSimilarity() - Constructor for class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.CovarianceDimensionSimilarity
Constructor.
CovarianceDimensionSimilarity.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity
Parameterization class.
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.
CoverageComparator() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace.CoverageComparator
 
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.
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
cross3D(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Cross product for 3d vectors, i.e.
cross3D(double[], double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Cross product for 3d vectors, i.e.
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.
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.
CSSFILE - Static variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
 
CSSFILE - Static variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
 
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<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<N> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial
Spatial outlier detection based on random walks.
CTLuRandomWalkEC(DistanceFunction<N>, 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.
cubicTo(Vector, Vector, Vector) - 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.visualization.gui.overview.PlotItem.ItmItr
 
curclu - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
Current clustering.
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.math.statistics.distribution.HaltonUniformDistribution
Current value
current - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.FilteredIter
Current object, if valid.
current - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.MergedParameterization
Parameters we used before, but have rewound
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.
CUTOFF - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS
Significance cutoff when computing kernel density.
cutoff - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS
Candidates limit.
cutoff - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.Parameterizer
Holds the value of HiCS.Parameterizer.LIMIT_ID.
cutoff - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.TopKOutlierScaling
The value we cut off at.
cycleLeftC(long, int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Rotate a long to the left, cyclic with length len
cycleLeftI(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Cycle a bitstring to the right.
cycleRightC(long, int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Rotate a long to the right, cyclic with length len
cycleRightI(long[], int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Cycle a bitstring to the right.
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ELKI Version 0.7.0~20150828

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