- n - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch
-
Number of biclusters to be found.
- n - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer
-
Number of biclusters to be found.
- n - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.ClusteringFeature
-
Number of objects
- n - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut
-
Number of outliers to compute exactly
- n - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.Parameterizer
-
Top-n candidates to compute exactly
- n - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.selection.FirstNStreamFilter
-
Remaining entries to keep
- n - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.selection.FirstNStreamFilter.Parameterizer
-
Number of objects to keep
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
-
Row and column dimension (square matrix).
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.LUDecomposition
-
Row and column dimensions, and pivot sign.
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter.FirstNEigenPairFilter
-
The threshold for strong eigenvectors: n eigenvectors with the n highest
eigenvalues are marked as strong eigenvectors.
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter.FirstNEigenPairFilter.Parameterizer
-
The number of eigenpairs to keep.
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.QRDecomposition
-
Row and column dimensions.
- n - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition
-
Row and column dimensions.
- n - Variable in class de.lmu.ifi.dbs.elki.math.Mean
-
Weight sum (number of samples).
- n - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution
-
Number of tries
- n - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution.Parameterizer
-
Number of trials.
- N_DEFAULT - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation.Parameterizer
-
Default number of folds.
- N_DEFAULT - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation.Parameterizer
-
Default number of folds.
- N_DEFAULT - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation.Parameterizer
-
Default number of folds.
- N_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer
-
Number of biclusters to be found.
- N_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.Parameterizer
-
Parameter to specify how many outliers should be computed
- N_ID - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution.Parameterizer
-
Number of trials.
- N_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.referencepoints.RandomGeneratedReferencePoints.Parameterizer
-
Parameter to specify the number of requested reference points.
- N_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.referencepoints.RandomSampleReferencePoints.Parameterizer
-
Parameter to specify the sample size.
- n_star - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut
-
Set sizes, total and current iteration
- NaiveAgglomerativeHierarchicalClustering1<O> - Class in tutorial.clustering
-
This tutorial will step you through implementing a well known clustering
algorithm, agglomerative hierarchical clustering, in multiple steps.
- NaiveAgglomerativeHierarchicalClustering1(DistanceFunction<? super O>, int) - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering1
-
Constructor.
- NaiveAgglomerativeHierarchicalClustering1.Parameterizer<O> - Class in tutorial.clustering
-
Parameterization class
- NaiveAgglomerativeHierarchicalClustering2<O> - Class in tutorial.clustering
-
This tutorial will step you through implementing a well known clustering
algorithm, agglomerative hierarchical clustering, in multiple steps.
- NaiveAgglomerativeHierarchicalClustering2(DistanceFunction<? super O>, int) - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering2
-
Constructor.
- NaiveAgglomerativeHierarchicalClustering2.Parameterizer<O> - Class in tutorial.clustering
-
Parameterization class
- NaiveAgglomerativeHierarchicalClustering3<O> - Class in tutorial.clustering
-
This tutorial will step you through implementing a well known clustering
algorithm, agglomerative hierarchical clustering, in multiple steps.
- NaiveAgglomerativeHierarchicalClustering3(DistanceFunction<? super O>, int, NaiveAgglomerativeHierarchicalClustering3.Linkage) - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3
-
Constructor.
- NaiveAgglomerativeHierarchicalClustering3.Linkage - Enum in tutorial.clustering
-
Different linkage strategies.
- NaiveAgglomerativeHierarchicalClustering3.Parameterizer<O> - Class in tutorial.clustering
-
Parameterization class
- NaiveAgglomerativeHierarchicalClustering4<O> - Class in tutorial.clustering
-
This tutorial will step you through implementing a well known clustering
algorithm, agglomerative hierarchical clustering, in multiple steps.
- NaiveAgglomerativeHierarchicalClustering4(DistanceFunction<? super O>, NaiveAgglomerativeHierarchicalClustering4.Linkage) - Constructor for class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4
-
Constructor.
- NaiveAgglomerativeHierarchicalClustering4.Linkage - Enum in tutorial.clustering
-
Different linkage strategies.
- NaiveAgglomerativeHierarchicalClustering4.Parameterizer<O> - Class in tutorial.clustering
-
Parameterization class
- NaiveMeanShiftClustering<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Mean-shift based clustering algorithm.
- NaiveMeanShiftClustering(DistanceFunction<? super V>, KernelDensityFunction, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.NaiveMeanShiftClustering
-
Constructor.
- NaiveMeanShiftClustering.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering
-
Parameterizer.
- NaiveProjectedKNNPreprocessor<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Compute the approximate k nearest neighbors using 1 dimensional projections.
- NaiveProjectedKNNPreprocessor(Relation<O>, double, int, RandomProjectionFamily, Random) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor
-
Constructor.
- NaiveProjectedKNNPreprocessor.Factory<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Index factory class
- NaiveProjectedKNNPreprocessor.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Parameterization class.
- NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
KNN Query processor for naive projections.
- NaiveProjectedKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery
-
Constructor.
- naiveQuery(V, WritableDoubleDataStore, HashSetModifiableDBIDs) - Method in class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex
-
Query the most similar objects, abstract version.
- naiveQueryDense(NumberVector, WritableDoubleDataStore, HashSetModifiableDBIDs) - Method in class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex
-
Query the most similar objects, dense version.
- naiveQuerySparse(SparseNumberVector, WritableDoubleDataStore, HashSetModifiableDBIDs) - Method in class de.lmu.ifi.dbs.elki.index.invertedlist.InMemoryInvertedIndex
-
Query the most similar objects, sparse version.
- name - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores
-
Constant column to prepend (may be null)
- name - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores.Parameterizer
-
Name column to prepend.
- name - Variable in class de.lmu.ifi.dbs.elki.data.Cluster
-
Cluster name.
- name - Variable in class de.lmu.ifi.dbs.elki.data.ExternalID
-
Object name
- name - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster
-
Cluster name
- name - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorStatic
-
Cluster name
- name - Variable in class de.lmu.ifi.dbs.elki.database.relation.MaterializedDoubleRelation
-
The relation name.
- name - Variable in class de.lmu.ifi.dbs.elki.database.relation.MaterializedRelation
-
The relation name.
- name - Variable in class de.lmu.ifi.dbs.elki.result.BasicResult
-
Result name, for presentation
- name - Variable in class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement
-
Measurement name.
- name - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID
-
Option name
- name - Variable in class de.lmu.ifi.dbs.elki.visualization.colors.ListBasedColorLibrary
-
Color scheme name
- name - Variable in class de.lmu.ifi.dbs.elki.visualization.css.CSSClass
-
CSS class name
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
-
A short name characterizing this Visualizer.
- name - Variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary
-
Style scheme name
- name - Variable in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask
-
Name
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotVisualizer
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer
-
CircleSegments visualizer name
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisReorderVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.BoundingBoxVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterParallelMeanVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.index.RTreeParallelVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.LineVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.ParallelAxisVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionAxisRangeVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionLineVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AxisVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterMeanVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterOrderVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterStarVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density.DensityEstimationOverlay
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeMBRVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.MarkerVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier.BubbleVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier.COPVectorVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.PolygonVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.ReferencePointsVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionConvexHullVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionDotVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipScoreVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainBoundingBoxVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainInstancesVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization
-
A short name characterizing this Visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization
-
Visualizer name.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.HistogramVisualization
-
Histogram visualizer name
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.KeyVisualization
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.PixmapVisualizer
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.SettingsVisualization
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.SimilarityMatrixVisualizer
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYCurveVisualization
-
Name for this visualizer.
- NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYPlotVisualization
-
Name for this visualizer.
- NAME_CLASS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipStringVisualization
-
A short name characterizing this Visualizer.
- NAME_EID - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipStringVisualization
-
A short name characterizing this Visualizer.
- NAME_GEN - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipScoreVisualization
-
A short name characterizing this Visualizer.
- NAME_ID - Static variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores.Parameterizer
-
Row name.
- NAME_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipStringVisualization
-
A short name characterizing this Visualizer.
- NAME_LABEL - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipStringVisualization
-
A short name characterizing this Visualizer.
- namefreq - Variable in class de.lmu.ifi.dbs.elki.result.textwriter.naming.SimpleEnumeratingScheme
-
Count how often each name occurred so far.
- names - Variable in class de.lmu.ifi.dbs.elki.result.textwriter.naming.SimpleEnumeratingScheme
-
Assigned cluster names.
- names - Variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry
-
Class names.
- NamingScheme - Interface in de.lmu.ifi.dbs.elki.result.textwriter.naming
-
Naming scheme implementation for clusterings.
- nandI(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
NOTAND o onto v in-place, i.e. v &= ~o
- NanoDuration - Class in de.lmu.ifi.dbs.elki.logging.statistics
-
Class that tracks the runtime of a task with System.nanoTime()
- NanoDuration(String) - Constructor for class de.lmu.ifi.dbs.elki.logging.statistics.NanoDuration
-
Constructor.
- nanpattern - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.CategorialDataAsNumberVectorParser
-
Pattern for NaN values.
- ncounter - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN
-
Number of neighbors.
- NDCGEvaluation - Class in de.lmu.ifi.dbs.elki.evaluation.scores
-
Normalized Discounted Cumulative Gain.
- NDCGEvaluation() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.NDCGEvaluation
-
- NDCGEvaluation.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.scores
-
Parameterization class.
- near - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.util.Arcball1DOFAdapter
-
Temp buffer we use for computations.
- nearest - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS.Assignment
-
Distance to the nearest medoid of each point.
- nearest - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPAM.Instance
-
Distance to the nearest medoid of each point.
- nearestMeans(double[][], int[][]) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans
-
Recompute the separation of cluster means.
- NearestNeighborAffinityMatrixBuilder<O> - Class in de.lmu.ifi.dbs.elki.algorithm.projection
-
Build sparse affinity matrix using the nearest neighbors only.
- NearestNeighborAffinityMatrixBuilder(DistanceFunction<? super O>, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Constructor.
- NearestNeighborAffinityMatrixBuilder(DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Constructor.
- NearestNeighborAffinityMatrixBuilder.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.projection
-
Parameterization class.
- needsMetric() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Parameterizer
-
Users could use other non-metric distances at their own risk; but some
k-means variants make explicit use of the triangle inequality, we emit
extra warnings then.
- needsMetric() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansCompare.Parameterizer
-
- needsMetric() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly.Parameterizer
-
- needsMetric() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansSimplifiedElkan.Parameterizer
-
- needsMetric() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansSort.Parameterizer
-
- needsTwoPass() - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.em.EMClusterModel
-
True, if the model needs two passes in the E step.
- needsTwoPass() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.TwoPassMultivariateGaussianModel
-
- needToInferCaller - Variable in class de.lmu.ifi.dbs.elki.logging.ELKILogRecord
-
Flag whether we still need to infer the caller.
- negative - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter
-
Label to return for negative matches.
- negative - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter.Parameterizer
-
Names for positive and negative classes.
- NEGATIVE_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter.Parameterizer
-
Class label to assign to negative instances.
- NEIGHBORHOOD_FILE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood.Factory.Parameterizer
-
Parameter to specify the neighborhood file
- NEIGHBORHOOD_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier
-
Parameter to specify the neighborhood predicate to use.
- NEIGHBORHOOD_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory.Parameterizer
-
Parameter to specify the neighborhood predicate to use.
- NEIGHBORHOOD_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted.LinearWeightedExtendedNeighborhood.Factory.Parameterizer
-
Parameter to specify the neighborhood predicate to use.
- neighborhoodDistanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.FlexibleLOF.Parameterizer
-
Neighborhood distance function.
- NEIGHBORHOODPRED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Parameter for neighborhood predicate.
- NEIGHBORHOODPRED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Parameter for neighborhood predicate.
- NEIGHBORLIST - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
A list of neighbors.
- NeighborPredicate<T> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Get the neighbors of an object
Note the Factory/Instance split of this interface.
- NeighborPredicate.Instance<T> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
-
Instance for a particular data set.
- NEIGHBORS_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS.Parameterizer
-
The number of neighbors to explore.
- NeighborSetPredicate - Interface in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
-
Predicate to obtain the neighbors of a reference object as set.
- NeighborSetPredicate.Factory<O> - Interface in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
-
Factory interface to produce instances.
- neighs - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.FastOPTICS
-
neighbors of a point
- newArray() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) array of DBIDs.
- newArray(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) array of DBIDs.
- newArray(DBIDs) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) array of DBIDs.
- newArray() - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) array of DBIDs.
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) array of DBIDs.
- newArray(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) array of DBIDs.
- newArray() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newArray(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newArray(DBIDs) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.DoubleMinMax
-
Generate a new array of initialized DoubleMinMax objects (with default
constructor)
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.IntegerMinMax
-
Generate a new array of initialized IntegerMinMax objects (with default
constructor)
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.Mean
-
Create and initialize a new array of MeanVariance
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.MeanVariance
-
Create and initialize a new array of MeanVariance
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.MeanVarianceMinMax
-
Create and initialize a new array of MeanVarianceMinMax
- newArray(int) - Static method in class de.lmu.ifi.dbs.elki.math.StatisticalMoments
-
Create and initialize a new array of MeanVariance
- newCluster(int, GeneratorInterface) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain.AssignLabelsByDensity
-
- newCluster(int, GeneratorInterface) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain.AssignPoint
-
Set the current cluster.
- newContext(ResultHierarchy, Result) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer
-
Make a new visualization context
- newCounter(String) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
-
Generate a new counter.
- newDistanceDBIDList(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Create a modifiable list to store distance-DBID pairs.
- newDistanceDBIDList() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Create a modifiable list to store distance-DBID pairs.
- newDistanceDBIDList(int) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Create a modifiable list to store distance-DBID pairs.
- newDistanceDBIDList() - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Create a modifiable list to store distance-DBID pairs.
- newDistanceDBIDList(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newDistanceDBIDList() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newDuration(String) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
-
Generate a new duration statistic.
- newe - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeReplaceByID
-
Replacement element.
- newe - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeSubstitute
-
Replacement element.
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.BitVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.ByteVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.DoubleVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends D, A>) - Method in interface de.lmu.ifi.dbs.elki.data.FeatureVector.Factory
-
Returns a new FeatureVector of V for the given values.
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.FloatVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.IntegerVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.OneDimensionalDoubleVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.ShortVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseByteVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseDoubleVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseFloatVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseShortVector.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.SimpleGaussianContinuousUncertainObject.Factory
-
- newFeatureVector(Random, A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier
-
- newFeatureVector(Random, A, NumberArrayAdapter<?, A>) - Method in interface de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.Uncertainifier
-
Generate a new uncertain object.
- newFeatureVector(Random, A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.UniformUncertainifier
-
- newFeatureVector(Random, A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.UnweightedDiscreteUncertainifier
-
- newFeatureVector(Random, A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.WeightedDiscreteUncertainifier
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.UniformContinuousUncertainObject.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.UnweightedDiscreteUncertainObject.Factory
-
- newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.WeightedDiscreteUncertainObject.Factory
-
- newGroup(String) - Method in class de.lmu.ifi.dbs.elki.result.EvaluationResult
-
Add a new measurement group.
- newHashSet() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet(DBIDs) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet() - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet(int) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new (modifiable) hash set of DBIDs.
- newHashSet() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newHashSet(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newHashSet(DBIDs) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newHeap(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Create an heap for kNN search.
- newHeap(KNNList) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Build a new heap from a given list.
- newHeap(int) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Create an appropriate heap for the distance type.
- newHeap(KNNList) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Build a new heap from a given list.
- newHeap(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newHeap(KNNList) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newids - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster
-
New ids, not yet in child clusters.
- NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.application.AbstractApplication
-
The newline string according to system.
- NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI
-
Newline used in output.
- NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Newline string.
- NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream
-
System newline character(s)
- NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
The system newline setting.
- NEWLINEC - Static variable in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger
-
Newline as char array.
- newmeans - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly.Instance
-
Temporary storage for the new means.
- newmeans - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansSimplifiedElkan.Instance
-
Scratch space for new means.
- newNode(FPGrowth.FPNode, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree
-
Create a new node of the FP-tree, linking it into the header table.
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.BitVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.BitVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.ByteVector.Factory
-
- newNumberVector(double[]) - Method in class de.lmu.ifi.dbs.elki.data.DoubleVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.DoubleVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.FloatVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.IntegerVector.Factory
-
- newNumberVector(double[]) - Method in interface de.lmu.ifi.dbs.elki.data.NumberVector.Factory
-
Returns a new NumberVector of N for the given values.
- newNumberVector(NumberVector) - Method in interface de.lmu.ifi.dbs.elki.data.NumberVector.Factory
-
Returns a new NumberVector of N for the given values.
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in interface de.lmu.ifi.dbs.elki.data.NumberVector.Factory
-
Instantiate from any number-array like object.
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.OneDimensionalDoubleVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.ShortVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseByteVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseByteVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseDoubleVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseDoubleVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseFloatVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseFloatVector.Factory
-
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in interface de.lmu.ifi.dbs.elki.data.SparseNumberVector.Factory
-
Returns a new NumberVector of N for the given values.
- newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.SparseShortVector.Factory
-
- newNumberVector(Int2DoubleOpenHashMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseShortVector.Factory
-
- newPageFile(Class<P>) - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCachePageFileFactory
-
- newPageFile(Class<P>) - Method in class de.lmu.ifi.dbs.elki.persistent.MemoryPageFileFactory
-
- newPageFile(Class<P>) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFileFactory
-
- newPageFile(Class<P>) - Method in interface de.lmu.ifi.dbs.elki.persistent.PageFileFactory
-
Make a new page file.
- newPageFile(Class<P>) - Method in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFileFactory
-
- newPair(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a DBID pair from two existing DBIDs.
- newPair(double, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a double-DBID pair.
- newPair(DBIDRef, DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a DBID pair.
- newPair(double, DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a DoubleDBIDPair.
- newPair(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newPair(double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- newStream(String) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput
-
Open a new stream of the given name
- newTree(DBIDs, Relation<? extends NumberVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree.Factory
-
Make a new tree.
- newValue - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.AttributeModifier
-
The new value of the attribute.
- newVar(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
-
Make a new DBID variable.
- newVar(DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new DBID variable.
- newVar() - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
-
Make a new DBID variable.
- newVar(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
-
- next - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepScanPosition
-
Variable for accessing.
- next() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepScanPosition
-
Advance to the next entry
- next - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.TrivialDBIDFactory
-
Keep track of the smallest dynamic DBID offset not used.
- next() - Method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.RelationObjectIterator
-
- next() - Method in class de.lmu.ifi.dbs.elki.index.tree.BreadthFirstEnumeration
-
Returns the next element of this enumeration if this enumeration object has
at least one more element to provide.
- next() - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator
-
- next(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.FastNonThreadsafeRandom
-
- next(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.Xoroshiro128NonThreadsafeRandom
-
- next(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift1024NonThreadsafeRandom
-
- next(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift64NonThreadsafeRandom
-
- next - Variable in class de.lmu.ifi.dbs.elki.utilities.xml.XMLNodeIterator
-
Store the next node
- next() - Method in class de.lmu.ifi.dbs.elki.utilities.xml.XMLNodeIterator
-
Return next and advance iterator.
- next() - Method in class de.lmu.ifi.dbs.elki.utilities.xml.XMLNodeListIterator
-
Return next and advance iterator.
- next - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.overview.PlotItem.ItmItr
-
- next() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.PlotItem.ItmItr
-
- nextAllOnesInt(int) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
-
Find the next larger number with all ones.
- nextAllOnesLong(long) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
-
Find the next larger number with all ones.
- nextClearBit(long, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the next clear bit.
- nextClearBit(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the next clear bit.
- nextclus - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
Next cluster number assigned.
- nextDouble() - Method in class de.lmu.ifi.dbs.elki.utilities.random.FastNonThreadsafeRandom
-
- nextDouble() - Method in class de.lmu.ifi.dbs.elki.utilities.random.Xoroshiro128NonThreadsafeRandom
-
- nextDouble() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift1024NonThreadsafeRandom
-
- nextDouble() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift64NonThreadsafeRandom
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleReader
-
- nextEvent() - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.BundleStreamSource
-
Get the next event
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.StreamFromBundle
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamConversionFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.DropNaNFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.NoMissingValuesFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.NoOpFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.selection.ByLabelFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.selection.FirstNStreamFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.selection.RandomSamplingStreamFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter
-
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.CategorialDataAsNumberVectorParser
-
- nextevent - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
Event to report next.
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
- nextevent - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Event to report next.
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
- nextevent - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
Event to report next.
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
-
- nextevent - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
-
Event to report next.
- nextEvent() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
-
- nextIndex(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.unionfind.WeightedQuickUnionInteger
-
Occupy the next unused index.
- nextInt() - Method in class de.lmu.ifi.dbs.elki.utilities.random.FastNonThreadsafeRandom
-
- nextInt(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.FastNonThreadsafeRandom
-
Returns a pseudorandom, uniformly distributed int value between 0
(inclusive) and the specified value (exclusive), drawn from this random
number generator's sequence.
- nextInt() - Method in class de.lmu.ifi.dbs.elki.utilities.random.Xoroshiro128NonThreadsafeRandom
-
- nextInt(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.Xoroshiro128NonThreadsafeRandom
-
Returns a pseudorandom, uniformly distributed int value between 0
(inclusive) and the specified value (exclusive), drawn from this random
number generator's sequence.
- nextInt() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift1024NonThreadsafeRandom
-
- nextInt(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift1024NonThreadsafeRandom
-
Returns a pseudorandom, uniformly distributed int value between 0
(inclusive) and the specified value (exclusive), drawn from this random
number generator's sequence.
- nextInt() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift64NonThreadsafeRandom
-
- nextInt(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift64NonThreadsafeRandom
-
Returns a pseudorandom, uniformly distributed int value between 0
(inclusive) and the specified value (exclusive), drawn from this random
number generator's sequence.
- nextIntRefined(int) - Method in class de.lmu.ifi.dbs.elki.utilities.random.FastNonThreadsafeRandom
-
Returns a pseudorandom, uniformly distributed int value between 0
(inclusive) and the specified value (exclusive), drawn from this random
number generator's sequence.
- nextIteration(double[][]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor
-
Initialize for a new iteration.
- nextLine() - Method in class de.lmu.ifi.dbs.elki.utilities.io.BufferedLineReader
-
Read the next line.
- nextLineExceptComments() - Method in class de.lmu.ifi.dbs.elki.utilities.io.TokenizedReader
-
Read the next line into the tokenizer.
- nextLong() - Method in class de.lmu.ifi.dbs.elki.utilities.random.Xoroshiro128NonThreadsafeRandom
-
- nextLong() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift1024NonThreadsafeRandom
-
- nextLong() - Method in class de.lmu.ifi.dbs.elki.utilities.random.XorShift64NonThreadsafeRandom
-
- nextPageID - Variable in class de.lmu.ifi.dbs.elki.persistent.AbstractStoringPageFile
-
The last page ID.
- nextPartitioning() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation
-
- nextPartitioning() - Method in interface de.lmu.ifi.dbs.elki.evaluation.classification.holdout.Holdout
-
Get the next partitioning of the given holdout.
- nextPartitioning() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.LeaveOneOut
-
- nextPartitioning() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation
-
- nextPartitioning() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation
-
- nextPosition(int, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Helper that is similar to Math.min(a,b), except that negative
values are considered "invalid".
- nextPow2Int(int) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
-
Find the next power of 2.
- nextPow2Int(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.HeapUtil
-
Find the next power of 2.
- nextPow2Long(long) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
-
Find the next power of 2.
- nextRadicalInverse() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
Compute the next radical inverse.
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.AbstractDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.CauchyDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ConstantDistribution
-
- nextRandom() - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution
-
Generate a new random value
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
-
This method currently uses the naive approach of returning
-log(uniform).
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
- nextRandom(double, double, Random) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
Generate a random value with the generators parameters.
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticAlternateDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GeneralizedLogisticDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GumbelDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.InverseGaussianDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.KappaDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LaplaceDistribution
-
This method currently uses the naive approach of returning
-log(uniform).
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogGammaDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogisticDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogLogisticDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.LogNormalDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.RayleighDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.SkewGeneralizedNormalDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.StudentsTDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.UniformDistribution
-
- nextRandom() - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.WeibullDistribution
-
- nextSearchItemset(BitVector, int[], int[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI
-
Advance scratch itemset to the next.
- nextSep(String, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.range.ParseIntRanges
-
Find the next separator.
- nextSetBit(long, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the next set bit.
- nextSetBit(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the next set bit.
- nextToken(StreamTokenizer) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser
-
Helper function for token handling.
- nf - Variable in class de.lmu.ifi.dbs.elki.algorithm.DependencyDerivator
-
Number format for output of solution.
- nf - Variable in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
-
Number format for output accuracy.
- NF - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Dynamic number formatter, but with language constraint.
- nf - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipScoreVisualization.Parameterizer
-
Number formatter used for visualization
- NF0 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (0 digits) for output purposes.
- NF16 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (16 digits) for output purposes.
- NF2 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (2 digits) for output purposes.
- NF3 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (3 digits) for output purposes.
- NF4 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (4 digits) for output purposes.
- NF6 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (6 digits) for output purposes.
- NF8 - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Number Formatter (8 digits) for output purposes.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation
-
Holds the number of folds, current fold.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation.Parameterizer
-
Holds the number of folds.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation
-
Holds the number of folds, current fold.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation.Parameterizer
-
Holds the number of folds.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation
-
Holds the number of folds, current fold.
- nfold - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation.Parameterizer
-
Holds the number of folds.
- NFOLD_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation.Parameterizer
-
Parameter for number of folds.
- NFOLD_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation.Parameterizer
-
Parameter for number of folds.
- NFOLD_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation.Parameterizer
-
Parameter for number of folds.
- nmea - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel
-
Temporary storage, to avoid reallocations.
- nmea - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel
-
Temporary storage, to avoid reallocations.
- nmea - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.SphericalGaussianModel
-
Temporary storage, to avoid reallocations.
- nmea - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix
-
Temporary storage, to avoid reallocations.
- nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.ALOCIQuadTree
-
Maximum fill for a page before splitting
- nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI
-
Minimum size for a leaf.
- nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer
-
Neighborhood minimum size
- nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI
-
Minimum neighborhood size.
- nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.Parameterizer
-
Minimum neighborhood size.
- NMIN_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer
-
Parameter to specify the minimum neighborhood size
- NMIN_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.Parameterizer
-
Parameter to specify the minimum neighborhood size
- nn - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.HilFeature
-
Heap with the nearest known neighbors
- nn_keys - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.HilFeature
-
Set representation of the nearest neighbors for faster lookups
- NNChain<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
-
NNchain clustering algorithm.
- NNChain(DistanceFunction<? super O>, Linkage) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.NNChain
-
Constructor.
- NNChain.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
-
Parameterization class.
- nnChainCore(MatrixParadigm, DBIDArrayMIter, DistanceQuery<O>, PointerHierarchyRepresentationBuilder, Int2ObjectOpenHashMap<ModifiableDBIDs>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.MiniMaxNNChain
-
Uses NNChain as in "Modern hierarchical, agglomerative clustering
algorithms" by Daniel Müllner
- nnChainCore(MatrixParadigm, PointerHierarchyRepresentationBuilder) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.NNChain
-
Uses NNChain as in "Modern hierarchical, agglomerative clustering
algorithms" by Daniel Müllner
- NNDescent<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
NN-desent (also known as KNNGraph) is an approximate nearest neighbor search
algorithm beginning with a random sample, then iteratively refining this
sample until.
- NNDescent(Relation<O>, DistanceFunction<? super O>, int, RandomFactory, double, double, boolean, int) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent
-
Constructor.
- NNDescent.Factory<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Index factory.
- NNDescent.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn
-
Parameterization class
- NO_EXPORT_ATTRIBUTE - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot
-
Attribute to block export of element.
- NO_PENALIZE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer
-
Do not penalize ignored noise.
- NO_PENALIZE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria.Parameterizer
-
Do not penalize ignored noise.
- NO_VALUE - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.UpdatableHeap
-
Constant for "not in heap".
- NO_VALUE - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil
-
Key not found value.
- NoAutomaticEvaluation - Class in de.lmu.ifi.dbs.elki.evaluation
-
No-operation evaluator, that only serves the purpose of explicitely disabling
the default value of
AutomaticEvaluation, if you do not want
evaluation to run.
- NoAutomaticEvaluation() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.NoAutomaticEvaluation
-
- NoAutomaticEvaluation.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation
-
Parameterization class
- nocenter - Variable in class de.lmu.ifi.dbs.elki.utilities.referencepoints.StarBasedReferencePoints
-
Exclude the center vector.
- nocenter - Variable in class de.lmu.ifi.dbs.elki.utilities.referencepoints.StarBasedReferencePoints.Parameterizer
-
- NOCENTER_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.referencepoints.StarBasedReferencePoints.Parameterizer
-
Parameter to specify the grid resolution.
- nocorrect - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi
-
Disable the predecessor correction.
- nocorrect - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.Parameterizer
-
- NOCORRECT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.Parameterizer
-
Parameter to disable the correction function.
- Node(int, double[], int, int, List<ALOCI.Node>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node
-
Constructor.
- Node(Parameter<?>, String, int, int) - Constructor for class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters.Node
-
Constructor.
- Node(DBIDRef, double, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree.Node
-
Constructor.
- Node(DBIDRef, double, double, DoubleDBIDList) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.CoverTree.Node
-
Constructor for leaf node.
- Node(DBIDRef, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree.Node
-
Constructor.
- Node(DBIDRef, double, DoubleDBIDList) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.SimplifiedCoverTree.Node
-
Constructor for leaf node.
- Node<E extends Entry> - Interface in de.lmu.ifi.dbs.elki.index.tree
-
This interface defines the common requirements of nodes in an index
structure.
- Node(int, List<CompactCircularMSTLayout3DPC.Node>) - Constructor for class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.CompactCircularMSTLayout3DPC.Node
-
Constructor.
- Node(int, List<MultidimensionalScalingMSTLayout3DPC.Node>) - Constructor for class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.MultidimensionalScalingMSTLayout3DPC.Node
-
Constructor.
- Node(int, List<SimpleCircularMSTLayout3DPC.Node>) - Constructor for class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.SimpleCircularMSTLayout3DPC.Node
-
Constructor.
- nodeAddition(double[][], ChengAndChurch.BiclusterCandidate) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch
-
Algorithm 3 of Cheng and Church.
- NodeAppendChild - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
Runnable wrapper for appending XML-Elements to existing Elements.
- NodeAppendChild(Element, Element) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeAppendChild
-
Trivial constructor.
- NodeAppendChild(Element, Element, SVGPlot, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeAppendChild
-
Full constructor.
- NodeArrayAdapter - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util
-
Access the entries of a node as array-like.
- NodeArrayAdapter() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util.NodeArrayAdapter
-
Constructor.
- nodeID - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query.MTreeSearchCandidate
-
Page id
- nodelist - Variable in class de.lmu.ifi.dbs.elki.utilities.xml.XMLNodeListIterator
-
The NodeList to iterate over.
- NodeReplaceAllChildren - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
Runnable wrapper to replace all children of a given node.
- NodeReplaceAllChildren(Element, Element) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeReplaceAllChildren
-
Trivial constructor.
- NodeReplaceAllChildren(Element, Element, SVGPlot, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeReplaceAllChildren
-
Full constructor.
- NodeReplaceByID - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
This helper class will replace a node in an SVG plot.
- NodeReplaceByID(Element, SVGPlot, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeReplaceByID
-
Setup a SVG node replacement.
- nodes - Variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree
-
Number of nodes in the tree (statistics only).
- nodes - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.Layout
-
Nodes
- nodeSplitter - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.RTreeSettings
-
The split strategy.
- NodeSubstitute - Class in de.lmu.ifi.dbs.elki.visualization.batikutil
-
This helper class will replace a node in an SVG plot.
- NodeSubstitute(Element, Element) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.NodeSubstitute
-
Setup a SVG node replacement.
- nofill - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Parameterizer
-
Fill parameter.
- NOFILL_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Parameterizer
-
Flag for half-transparent filling of selection cubes.
- noIncrementalRedraw - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
-
Flag to disallow an incremental redraw
- noInitialNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent.Factory
-
set initial neighbors?
- noInitialNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent.Factory.Parameterizer
-
No initial neighbors
- noInitialNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent
-
Do not use initial neighbors
- noise - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN
-
Holds a set of noise.
- NOISE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance
-
Noise IDs
- NOISE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC
-
Constants used internally.
- NOISE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance
-
Noise IDs.
- noise - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering
-
Holds a set of noise.
- noise - Variable in class de.lmu.ifi.dbs.elki.data.Cluster
-
Noise?
- noise1 - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
-
Noise flags
- noise2 - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
-
Noise flags
- NOISE_FLAG_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansMinusMinus.Parameterizer
-
Flag to produce a "noise" cluster, instead of assigning them to the
nearest neighbor.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering.Parameterizer
-
Parameter to specify the pattern to recognize noise clusters by.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering.Parameterizer
-
Parameter to specify the pattern to recognize noise clusters with.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.Parameterizer
-
Parameter flag for special noise handling.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer
-
Parameter for the option, how noise should be treated.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer
-
Parameter for the option, how noise should be treated.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer
-
Parameter for the option, how noise should be treated.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer
-
Parameter for the option, how noise should be treated.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer
-
Parameter to treat noise as a single cluster.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer
-
Parameter to treat noise as a single cluster.
- NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria.Parameterizer
-
Parameter for the option, how noise should be treated.
- noiseDim - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH
-
Holds the dimensionality for noise.
- noisedistribution - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter
-
Nature of the noise distribution.
- NoiseDistribution() - Constructor for enum de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter.NoiseDistribution
-
- noisedistribution - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter.Parameterizer
-
The option which nature of noise distribution to choose.
- NOISEDISTRIBUTION_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter.Parameterizer
-
Parameter for selecting the noise distribution.
- noiseFlag - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansMinusMinus
-
Create a noise cluster, otherwise assign to the nearest cluster.
- noiseFlag - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansMinusMinus.Parameterizer
-
Noise cluster flag.
- noiseHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
-
Option for noise handling.
- noiseHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer
-
Option, how noise should be treated.
- noiseHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex
-
Option for noise handling.
- noiseHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer
-
Option, how noise should be treated.
- NoiseHandling - Enum in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
-
Options for handling noise in internal measures.
- NoiseHandling() - Constructor for enum de.lmu.ifi.dbs.elki.evaluation.clustering.internal.NoiseHandling
-
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.SilhouetteOutlierDetection
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.SilhouetteOutlierDetection.Parameterizer
-
Noise handling
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer
-
Option, how noise should be treated.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer
-
Option, how noise should be treated.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer
-
Noise handling
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette.Parameterizer
-
Option, how noise should be treated.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors
-
Handling of Noise clusters
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer
-
Handling of noise clusters.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria
-
Option for noise handling.
- noiseOption - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria.Parameterizer
-
Option, how noise should be treated.
- noisepat - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering.Parameterizer
-
Pattern to recognize noise clusters by.
- noisepat - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering.Parameterizer
-
Pattern to recognize noise clusters with
- noisepattern - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering
-
Pattern to recognize noise clusters by.
- noisepattern - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering
-
Pattern to recognize noise clusters with.
- noiseSpecialHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering
-
Apply special handling to noise "clusters".
- noiseSpecialHandling - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.Parameterizer
-
Apply special handling to noise "clusters".
- NOKEEPMED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.Parameterizer
-
Draw independent samples.
- NOKEEPMED_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARA.Parameterizer
-
Draw independent samples.
- NOLOG_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeFactory.Parameterizer
-
Parameter for nolog
- nominateNeighbors(DBIDIter, DBIDArrayIter, double[], double, WritableDoubleDataStore) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.SOS
-
Vote for neighbors not being outliers.
- nominateNeighbors(DBIDIter, DBIDArrayIter, double[], double, WritableDoubleDataStore) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.ISOS
-
Vote for neighbors not being outliers.
- NoMissingValuesFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.cleaning
-
A filter to remove entries that have missing values.
- NoMissingValuesFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.NoMissingValuesFilter
-
Constructor.
- NoMissingValuesFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.cleaning
-
Parameterization class.
- NON_NEGATIVE - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.HellingerDistanceFunction
-
Assertion error message.
- NON_SPATIAL_DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier.Parameterizer
-
Parameter to specify the non spatial distance function to use
- NONBREAKING_SPACE - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil
-
Non-breaking unicode space character.
- NonFlatRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends RTreeSettings> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants
-
Abstract superclass for all non-flat R*-Tree variants.
- NonFlatRStarTree(PageFile<N>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.NonFlatRStarTree
-
Constructor.
- nonindexedClasses() - Static method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner
-
Get a list with all classes in the working folder (not including jars!)
- NonNumericFeaturesException - Exception in de.lmu.ifi.dbs.elki.datasource.filter.normalization
-
An exception to signal the encounter of non numeric features where numeric
features have been expected.
- NonNumericFeaturesException() - Constructor for exception de.lmu.ifi.dbs.elki.datasource.filter.normalization.NonNumericFeaturesException
-
An exception to signal the encounter of non numeric features where numeric
features have been expected.
- NonNumericFeaturesException(String) - Constructor for exception de.lmu.ifi.dbs.elki.datasource.filter.normalization.NonNumericFeaturesException
-
An exception to signal the encounter of non numeric features where numeric
features have been expected.
- NonNumericFeaturesException(Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.datasource.filter.normalization.NonNumericFeaturesException
-
An exception to signal the encounter of non numeric features where numeric
features have been expected.
- NonNumericFeaturesException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.datasource.filter.normalization.NonNumericFeaturesException
-
An exception to signal the encounter of non numeric features where numeric
features have been expected.
- nonSpatialDistanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier
-
The distance function to use
- nonZeroPivotSearch(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
-
Method for trivial pivot search, searches for non-zero entry.
- NoOpFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter
-
Dummy filter that doesn't do any filtering.
- NoOpFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.NoOpFilter
-
Constructor.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.LatLngAsECEFIndex.Factory
-
Disable refinement of distances.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.LatLngAsECEFIndex.Factory.Parameterizer
-
Disable refinement of distances.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.LngLatAsECEFIndex.Factory.Parameterizer
-
Disable refinement of distances.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory
-
Disable refinement of distances.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory.Parameterizer
-
Disable refinement of distances.
- norefine - Variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex
-
Refinement disable flag.
- norm - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.LengthNormalization
-
Norm to use.
- norm - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.LengthNormalization.Parameterizer
-
Norm to use.
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.MahalanobisDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.MatrixWeightedQuadraticDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPIntegerNormDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPNormDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.ManhattanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MaximumDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MinimumDistanceFunction
-
- norm(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseEuclideanDistanceFunction
-
- norm(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseLPNormDistanceFunction
-
- norm(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseManhattanDistanceFunction
-
- norm(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseMaximumDistanceFunction
-
- norm(SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseSquaredEuclideanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SquaredEuclideanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedEuclideanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedLPNormDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedManhattanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedMaximumDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedSquaredEuclideanDistanceFunction
-
- Norm<O> - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Abstract interface for a mathematical norm.
- norm(O) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.Norm
-
Compute the norm of object obj.
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceEuclideanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceLPNormDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceManhattanDistanceFunction
-
- norm(NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceMaximumDistanceFunction
-
- norm - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.KDTreeKNNQuery
-
Norm to use.
- norm - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree.KDTreeRangeQuery
-
Norm to use.
- norm - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree.KDTreeKNNQuery
-
Norm to use.
- norm - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree.KDTreeRangeQuery
-
Norm to use.
- norm2() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition
-
Two norm
- NORM_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise.LengthNormalization.Parameterizer
-
Option ID for normalization norm.
- NormalDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Gaussian distribution aka normal distribution
- NormalDistribution(double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
Constructor for Gaussian distribution
- NormalDistribution(double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
Constructor for Gaussian distribution
- NormalDistribution(double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
-
Constructor for Gaussian distribution
- NormalDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
-
Parameterization class
- Normalization<O> - Interface in de.lmu.ifi.dbs.elki.datasource.filter.normalization
-
Normalization performs a normalization on a set of feature vectors and is
capable to transform a set of feature vectors to the original attribute
ranges.
- normalize(int, double) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMADNormalization
-
Normalize a single dimension.
- normalize(int, double) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization
-
Normalize a single dimension.
- normalize(int, double) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization
-
Normalize a single dimension.
- normalize - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser
-
Normalize.
- normalize - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser.Parameterizer
-
Normalization flag.
- normalize(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Normalizes v1 to the length of 1.0.
- normalize - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierGammaScaling
-
Store flag to Normalize data before curve fitting.
- normalize - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierGammaScaling.Parameterizer
-
Store flag to Normalize data before curve fitting.
- NORMALIZE_FLAG - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser.Parameterizer
-
Option ID for normalization.
- NORMALIZE_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierGammaScaling.Parameterizer
-
Normalization flag.
- normalizeColumns(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Normalizes the columns of this matrix to length of 1.0.
- NORMALIZED_SIMILARITY - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter.Parameterizer
-
Normalized similarity functions
- NormalizedLevenshteinDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.strings
-
Levenshtein distance on strings, normalized by string length.
- NormalizedLevenshteinDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.strings.NormalizedLevenshteinDistanceFunction
-
Deprecated.
- NormalizedLevenshteinDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.strings
-
Parameterization class.
- NormalizedPrimitiveSimilarityFunction<O> - Interface in de.lmu.ifi.dbs.elki.distance.similarityfunction
-
Marker interface for similarity functions working on primitive objects, and
limited to the 0-1 value range.
- NormalizedSimilarityFunction<O> - Interface in de.lmu.ifi.dbs.elki.distance.similarityfunction
-
Marker interface to signal that the similarity function is normalized to
produce values in the range of [0:1].
- normalizedVariationOfInformation() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
-
Get the normalized variation of information (normalized, 0 = equal) NVI = 1
- NMI_Joint
X.
- normalizeEquals(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Normalizes v1 to the length of 1.0 in place.
- normalizeLMR(double[], int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.ProbabilityWeightedMoments
-
Normalize the moments
- normalizeScore(double) - Method in class de.lmu.ifi.dbs.elki.result.outlier.BasicOutlierScoreMeta
-
- normalizeScore(double) - Method in class de.lmu.ifi.dbs.elki.result.outlier.InvertedOutlierScoreMeta
-
- normalizeScore(double) - Method in interface de.lmu.ifi.dbs.elki.result.outlier.OutlierScoreMeta
-
Return a normalized value of the outlier score.
- normalizeScore(double) - Method in class de.lmu.ifi.dbs.elki.result.outlier.ProbabilisticOutlierScore
-
- NormalLevenbergMarquardtKDEEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Distribution parameter estimation using Levenberg-Marquardt iterative
optimization and a kernel density estimation.
- NormalLevenbergMarquardtKDEEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLevenbergMarquardtKDEEstimator
-
Constructor.
- NormalLevenbergMarquardtKDEEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Parameterization class.
- NormalLMMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Estimate the parameters of a normal distribution using the method of
L-Moments (LMM).
- NormalLMMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLMMEstimator
-
Constructor.
- NormalLMMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Parameterization class.
- NormalMADEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Estimator using Medians.
- NormalMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMADEstimator
-
Constructor.
- NormalMADEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Parameterization class.
- NormalMOMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Naive maximum-likelihood estimations for the normal distribution using mean
and sample variance.
- NormalMOMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMOMEstimator
-
Private constructor, use static instance!
- NormalMOMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
-
Parameterization class.
- normAngle(double) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil
-
Normalize an angle to [0:2pi[
- normF(double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
-
Frobenius norm
- noself - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel.LOFProcessor
-
Exclude object itself from computation.
- NoSupportedDataTypeException - Exception in de.lmu.ifi.dbs.elki.data.type
-
Exception thrown when no supported data type was found.
- NoSupportedDataTypeException(TypeInformation, Collection<TypeInformation>) - Constructor for exception de.lmu.ifi.dbs.elki.data.type.NoSupportedDataTypeException
-
Constructor.
- NoSupportedDataTypeException(String) - Constructor for exception de.lmu.ifi.dbs.elki.data.type.NoSupportedDataTypeException
-
Constructor with string message.
- NOT_A_NUMBER - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.ParseUtil
-
Preallocated exceptions.
- NOT_SELECTED - Static variable in interface de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.CellVisitor
-
Different modes of operation.
- NOT_SET - Static variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.Flag
-
Constant indicating that the flag is not set.
- notifyFactories(Object) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext
-
Notify factories of a change.
- NotImplementedException - Exception in de.lmu.ifi.dbs.elki.utilities.exceptions
-
Exception thrown when a particular code path was not yet implemented.
- NotImplementedException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.NotImplementedException
-
Constructor.
- NotImplementedException(String) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.NotImplementedException
-
Constructor.
- NotImplementedException() - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.NotImplementedException
-
"Not implemented yet" exception.
- nozeros - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceQuantileSampler
-
Flag to ignore zero distances (recommended with many duplicates).
- nozeros - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceQuantileSampler.Parameterizer
-
Flag to ignore zero distances (recommended with many duplicates).
- nozeros - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierLinearScaling
-
Ignore zero values
- nozeros - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierLinearScaling.Parameterizer
-
Ignore zero values
- NOZEROS_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceQuantileSampler.Parameterizer
-
Flag to ignore zero distances (recommended with many duplicates).
- NOZEROS_ID - Static variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierLinearScaling.Parameterizer
-
Flag to use ignore zeros when computing the min and max.
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance
-
The neighborhood predicate
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN
-
The neighborhood predicate factory.
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Parameterizer
-
Neighborhood predicate.
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
The neighborhood predicate
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN
-
The neighborhood predicate factory.
- npred - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Parameterizer
-
Neighborhood predicate.
- npredf - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier
-
Our predicate to obtain the neighbors
- npredf - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier.Parameterizer
-
The predicate to obtain the neighbors.
- npreds - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.parallel.ParallelGeneralizedDBSCAN.Instance
-
Factory for neighbor predicates.
- nu - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.svm.LibSVMOneClassOutlierDetection
-
Nu parameter.
- nu - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.svm.LibSVMOneClassOutlierDetection.Parameterizer
-
Nu parameter.
- nu - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.StudentsTDistribution.Parameterizer
-
Parameters.
- NU_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.svm.LibSVMOneClassOutlierDetection.Parameterizer
-
SVM nu parameter
- NU_ID - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.StudentsTDistribution.Parameterizer
-
Degrees of freedom.
- NullAlgorithm - Class in de.lmu.ifi.dbs.elki.algorithm
-
Null Algorithm, which does nothing.
- NullAlgorithm() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.NullAlgorithm
-
Constructor.
- nullIndividuum(int) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum
-
Create a "null" individuum (full space).
- NULLMSG - Variable in class de.lmu.ifi.dbs.elki.logging.ErrorFormatter
-
Null error message.
- NULLPOSTFIX - Static variable in class de.lmu.ifi.dbs.elki.result.textwriter.naming.SimpleEnumeratingScheme
-
This is the postfix added to the first cluster, which will be removed when
there is only one cluster of this name.
- num - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.util.Core
-
Cluster number
- num - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.FeatureBagging
-
Number of instances to use.
- num - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.FeatureBagging.Parameterizer
-
Number of instances to use.
- NUM_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.FeatureBagging.Parameterizer
-
Parameter to specify the number of instances to use in the ensemble.
- NUM_PRECISION - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution
-
Numerical precision to use
- NUM_PRECISION - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
-
Numerical precision to use (data type dependent!)
- NUMBER_OF_NEIGHBORS_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory
-
Parameter to indicate the number of neighbors to be taken into account
for the shared-nearest-neighbor similarity.
- NUMBER_PATTERN - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat
-
A pattern catching most numbers that can be parsed using
Double.parseDouble:
Some examples: 1 1.
- NUMBER_SELECTED_ATTRIBUTES_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.NumberVectorRandomFeatureSelectionFilter.Parameterizer
-
Parameter for the desired cardinality of the subset of attributes
selected for projection.
- NUMBER_VECTOR_FIELD - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
Input type for algorithms that require number vector fields.
- NUMBER_VECTOR_FIELD_1D - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
Type request for two-dimensional number vectors
- NUMBER_VECTOR_FIELD_2D - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
Type request for two-dimensional number vectors
- NUMBER_VECTOR_VARIABLE_LENGTH - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
-
Number vectors of variable length.
- NumberArrayAdapter<N extends java.lang.Number,A> - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike
-
Adapter for arrays of numbers, to avoid boxing.
- NUMBERLISTADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil
-
Static instance for lists of numbers.
- numberListAdapter(List<? extends T>) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil
-
Cast the static instance.
- NumberListArrayAdapter<T extends java.lang.Number> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike
-
Static adapter class to use a List in an array of number
API.
- NumberListArrayAdapter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.NumberListArrayAdapter
-
Constructor.
- numberOfBuckets - Variable in class de.lmu.ifi.dbs.elki.index.lsh.InMemoryLSHIndex.Instance
-
Number of buckets to use.
- numberOfBuckets - Variable in class de.lmu.ifi.dbs.elki.index.lsh.InMemoryLSHIndex
-
Number of buckets to use.
- numberOfBuckets - Variable in class de.lmu.ifi.dbs.elki.index.lsh.InMemoryLSHIndex.Parameterizer
-
Number of buckets to use.
- numberOfFeatureVectors() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit
-
Returns the number of feature vectors this unit contains.
- numberOfFreeParameters(Relation<? extends NumberVector>, Clustering<? extends MeanModel>) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.AbstractKMeansQualityMeasure
-
Compute the number of free parameters.
- numberOfLeadingZeros(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros.
- numberOfLeadingZeros(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros; 64 if all zero
Note: this the same as Long.numberOfLeadingZeros(long).
- numberOfLeadingZeros(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros; 32 if all zero
Note: this the same as Integer.numberOfLeadingZeros(int).
- numberOfLeadingZerosSigned(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros.
- numberOfLeadingZerosSigned(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros; -1 if all zero
Note: this has different semantics to Long.numberOfLeadingZeros(long)
when the number is 0.
- numberOfLeadingZerosSigned(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of leading zeros; -1 if all zero
Note: this has different semantics to Long.numberOfLeadingZeros(long)
when the number is 0.
- numberOfNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory
-
Holds the number of nearest neighbors to be used.
- numberOfNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory.Parameterizer
-
Holds the number of nearest neighbors to be used.
- numberOfNeighbors - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor
-
Holds the number of nearest neighbors to be used.
- numberOfNeighbours - Variable in class de.lmu.ifi.dbs.elki.algorithm.projection.NearestNeighborAffinityMatrixBuilder
-
Number of neighbors to use.
- numberOfPartitions() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation
-
- numberOfPartitions() - Method in interface de.lmu.ifi.dbs.elki.evaluation.classification.holdout.Holdout
-
How many partitions to test.
- numberOfPartitions() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.LeaveOneOut
-
- numberOfPartitions() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.RandomizedCrossValidation
-
- numberOfPartitions() - Method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation
-
- numberOfTrailingZeros(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of trailing zeros.
- numberOfTrailingZeros(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of trailing zeros.
- numberOfTrailingZeros(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of trailing zeros.
- numberOfTrailingZerosSigned(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of trailing zeros.
- numberOfTrailingZerosSigned(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.BitsUtil
-
Find the number of trailing zeros.
- NumberParameter<THIS extends NumberParameter<THIS,T>,T extends java.lang.Number> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters
-
Abstract class for defining a number parameter.
- NumberParameter(OptionID, T) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.NumberParameter
-
Constructs a number parameter with the given optionID and default Value.
- NumberParameter(OptionID, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.NumberParameter
-
Constructs a number parameter with the given optionID and optional flag.
- NumberParameter(OptionID) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.NumberParameter
-
Constructs a number parameter with the given optionID.
- numberSharedLevels(long[], long[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.HilbertFeatures
-
Number of levels shared
- NumberVector - Interface in de.lmu.ifi.dbs.elki.data
-
Interface NumberVector defines the methods that should be implemented by any
Object that is element of a real vector space of type N.
- NumberVector.Factory<V extends NumberVector> - Interface in de.lmu.ifi.dbs.elki.data
-
Factory API for this feature vector.
- NUMBERVECTORADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil
-
Use a number vector in the array API.
- NumberVectorAdapter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike
-
Adapter to use a feature vector as an array of features.
- NumberVectorAdapter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.NumberVectorAdapter
-
Constructor.
- NumberVectorDistanceFunction<O> - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction
-
Base interface for the common case of distance functions defined on numerical
vectors.
- NumberVectorFeatureSelectionFilter<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Parser to project the ParsingResult obtained by a suitable base parser onto a
selected subset of attributes.
- NumberVectorFeatureSelectionFilter(long[]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.NumberVectorFeatureSelectionFilter
-
Constructor.
- NumberVectorFeatureSelectionFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Parameterization class.
- NumberVectorLabelParser<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Parser for a simple CSV type of format, with columns separated by the given
pattern (default: whitespace).
- NumberVectorLabelParser(CSVReaderFormat, long[], NumberVector.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Constructor.
- NumberVectorLabelParser(NumberVector.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Constructor with defaults.
- NumberVectorLabelParser(Pattern, String, Pattern, long[], NumberVector.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
-
Constructor.
- NumberVectorLabelParser.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.parser
-
Parameterization class.
- NumberVectorRandomFeatureSelectionFilter<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Parser to project the ParsingResult obtained by a suitable base parser onto a
randomly selected subset of attributes.
- NumberVectorRandomFeatureSelectionFilter(int, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.NumberVectorRandomFeatureSelectionFilter
-
Constructor.
- NumberVectorRandomFeatureSelectionFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform
-
Parameterization class.
- numbin - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses
-
Number of bins to use in sampling.
- numbin - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer
-
Number of bins to use in sampling.
- numbins - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality
-
Number of bins to use.
- numbins - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality.Parameterizer
-
Number of bins to use.
- numbins - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.RankingQualityHistogram
-
Number of bins to use.
- numbins - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.RankingQualityHistogram.Parameterizer
-
Number of bins.
- numc - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec
-
Number of parents, number of children.
- numCandidates - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy
-
Number of candidates to consider
- numCandidates - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy.Parameterizer
-
The number of candidates to use
- numchildren - Variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode
-
Key, weight, and number of children.
- numChildren(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
-
- numChildren(O) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.Hierarchy
-
Get number of children
- numChildren() - Method in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.AbstractLayout3DPC.AbstractNode
-
- numChildren() - Method in interface de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.Layout.Node
-
Get the number of children.
- numCl - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ClustersWithNoiseExtraction
-
Minimum number of clusters.
- numCl - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ClustersWithNoiseExtraction.Parameterizer
-
Minimum number of clusters.
- numclusters - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segments
-
Number of Clusters for each clustering
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering1
-
Threshold, how many clusters to extract.
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering1.Parameterizer
-
Desired number of clusters.
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering2
-
Threshold, how many clusters to extract.
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering2.Parameterizer
-
Desired number of clusters.
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3
-
Threshold, how many clusters to extract.
- numclusters - Variable in class tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3.Parameterizer
-
Desired number of clusters.
- numelems - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
-
Number of all elements.
- numEntries - Variable in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode
-
The number of entries in this node.
- NumericalFeatureSelection<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.data.projection
-
Projection class for number vectors.
- NumericalFeatureSelection(int[]) - Constructor for class de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection
-
Constructor.
- NumericalFeatureSelection(BitSet) - Constructor for class de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection
-
Constructor.
- NumericalFeatureSelection.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.data.projection
-
Parameterization class.
- numfit - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod
-
Number of parameters to fit
- numLines() - Method in class de.lmu.ifi.dbs.elki.result.EvaluationResult
-
Number of lines recommended for display.
- numlocal - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS
-
Number of samples to draw (i.e. restarts).
- numlocal - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARANS.Parameterizer
-
Number of restarts to do.
- numObjects() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval
-
Returns the number of objects associated with this interval.
- nump - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec
-
Number of parents, number of children.
- numparams - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod
-
Number of parameters
- numParents(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
-
- numParents(O) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.Hierarchy
-
Get number of (direct) parents
- numpart - Variable in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.Factory
-
Number of partitions.
- numpart - Variable in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.Factory.Parameterizer
-
Number of partitions.
- numpart - Variable in class de.lmu.ifi.dbs.elki.index.vafile.VAFile.Factory
-
Number of partitions.
- numpart - Variable in class de.lmu.ifi.dbs.elki.index.vafile.VAFile.Factory.Parameterizer
-
Number of partitions.
- numPoints(Clustering<? extends MeanModel>) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.AbstractKMeansQualityMeasure
-
Compute the number of points in a given set of clusters (which may be
less than the complete data set for X-means!)
- numpos - Variable in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.VectorOverThreshold
-
Number of positive values.
- numpos - Variable in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.VectorZero
-
Number of positive values.
- numPositive() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DBIDsTest
-
- numPositive() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.VectorOverThreshold
-
- numPositive() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.VectorZero
-
- numPositive() - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation.Predicate
-
Return the number of positive ids.
- NUMPROJ_ID - Static variable in class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.AbstractProjectedHashFunctionFamily.Parameterizer
-
Number of projections to use in each hash function.
- NUMPROJ_ID - Static variable in class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.CosineHashFunctionFamily.Parameterizer
-
Number of projections to use in each hash function.
- numrecs - Variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskArray
-
Number of records in the file.
- numref - Variable in class de.lmu.ifi.dbs.elki.index.idistance.InMemoryIDistanceIndex
-
Number of reference points.
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA
-
Number of samples to draw (i.e. iterations).
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.Parameterizer
-
Number of samples to draw (i.e. iterations).
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARA
-
Number of samples to draw (i.e. iterations).
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARA.Parameterizer
-
Number of samples to draw (i.e. iterations).
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering
-
How many clusterings shall be made for aggregation.
- numsamples - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer
-
Field to store parameter the number of samples.
- NUMSAMPLES_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA.Parameterizer
-
The number of samples to run.
- NUMSAMPLES_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.FastCLARA.Parameterizer
-
The number of samples to run.
- NUMSTYLES - Static variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler
-
Number of styles to use (lower reduces rendering complexity a bit)
- numterms - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
-
Number of different terms observed.
- numterms - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
-
Number of different terms observed.
- numterms - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser
-
Number of different terms observed.
- numties - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNHeap
-
Number of element in ties list.
