N-Index (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

N

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.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.math.linearalgebra.CholeskyDecomposition: Row and column dimension (square matrix).
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.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.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.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.
namecount - 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.BitsUtil: NOTAND o onto v inplace, 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.
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: 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.
NEIGHBORLIST - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: A list of neighbors.
NeighborPredicate - 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.
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
newArray(Class<? extends T>, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Make a new array of the given class and size.
newArray(T[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Clone an array of the given type.
newArrayOfEmptyArrayList(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Create an array of len empty ArrayLists.
newArrayOfEmptyHashSet(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Create an array of len empty HashSets.
newArrayOfNull(int, Class<T>) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Create an array (of null values) This is a common unchecked cast we have to do due to Java Generics limitations.
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
newFeatureVector(A, ArrayAdapter<? extends Number, A>) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.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.
newInstance(T) - Static method in class de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil: Generic newInstance that tries to clone an object.
NEWLINE - Static variable in class de.lmu.ifi.dbs.elki.application.AbstractApplication: The newline string according to system.
newline - Variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters.WikiStream
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.FormatUtil: The system newline setting.
NEWLINEC - Static variable in class de.lmu.ifi.dbs.elki.logging.OutputStreamLogger: Newline as char array.
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(double[]) - Method in class de.lmu.ifi.dbs.elki.data.AbstractNumberVector.Factory
newNumberVector(NumberVector) - Method in class de.lmu.ifi.dbs.elki.data.AbstractNumberVector.Factory
newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.data.BitVector.Factory
newNumberVector(TIntDoubleMap, 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(TIntDoubleMap, 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(TIntDoubleMap, 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(TIntDoubleMap, 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(TIntDoubleMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector.Factory
newNumberVector(TIntDoubleMap, 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(TIntDoubleMap, int) - Method in class de.lmu.ifi.dbs.elki.data.SparseShortVector.Factory
newNumberVector(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.Factory
newNumberVector(A, NumberArrayAdapter<?, ? super A>) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.Factory
newNumberVector(NumberVector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.Factory
newPageFile(Class) - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCachePageFileFactory
newPageFile(Class) - Method in class de.lmu.ifi.dbs.elki.persistent.MemoryPageFileFactory
newPageFile(Class) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFileFactory
newPageFile(Class) - Method in interface de.lmu.ifi.dbs.elki.persistent.PageFileFactory: Make a new page file.
newPageFile(Class) - 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
newPairArray(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.pairs.Pair: Create a new array of the given size (for generics)
newStream(String) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput: Open a new stream of the given name
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(int) - Method in class de.lmu.ifi.dbs.elki.math.random.FastNonThreadsafeRandom
next(int) - Method in class de.lmu.ifi.dbs.elki.math.random.XorShift1024NonThreadsafeRandom
next(int) - Method in class de.lmu.ifi.dbs.elki.math.random.XorShift64NonThreadsafeRandom
next() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.FilteredIter: Java iterator style, because we need to "peek" the next element.
next() - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator
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.BitsUtil: Find the next clear bit.
nextClearBit(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the next clear bit.
nextElement() - 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.
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.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
nextIteration(List<Vector>) - 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.math.random.XorShift1024NonThreadsafeRandom
nextLong() - Method in class de.lmu.ifi.dbs.elki.math.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.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.
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.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.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.LogGammaAlternateDistribution
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.WaldDistribution
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.
nextSetBit(long, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the next set bit.
nextSetBit(long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.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.FormatUtil: Number Formatter (0 digits) for output purposes.
NF2 - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Number Formatter (2 digits) for output purposes.
NF3 - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Number Formatter (3 digits) for output purposes.
NF4 - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Number Formatter (4 digits) for output purposes.
NF6 - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Number Formatter (6 digits) for output purposes.
NF8 - Static variable in class de.lmu.ifi.dbs.elki.utilities.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: Holds the value of LOCI.NMIN_ID.
nmin - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.Parameterizer
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: 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
NO_CLASS_RESTRICTION - Static variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
NO_DEFAULT_VALUE - Static variable in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
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: Holds the value of StarBasedReferencePoints.Parameterizer.NOCENTER_ID.
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, Vector, 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.
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.query.DoubleDistanceSearchCandidate: Page id
nodeID - Variable in class de.lmu.ifi.dbs.elki.index.tree.query.GenericMTreeDistanceSearchCandidate: Node 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).
nodeSplitter - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRTreeSettings: 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.
NoDuplicateValueGlobalConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints: Global parameter constraint specifying that parameters of a list of number parameters (NumberParameter) are not allowed to have the same value.
NoDuplicateValueGlobalConstraint(List<? extends AbstractParameter<?, ?>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.NoDuplicateValueGlobalConstraint: Constructs a Not-Equal-Value global parameter constraint.
NoDuplicateValueGlobalConstraint(AbstractParameter<?, ?>...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.NoDuplicateValueGlobalConstraint: Constructs a Not-Equal-Value global parameter constraint.
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
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 - 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_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering: Pattern to recognize noise clusters by.
NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering: Pattern to recognize noise clusters with
NOISE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering: 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.
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
noisepat - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering.Parameterizer
noisepattern - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering: Holds the value of ByLabelClustering.NOISE_ID.
noisepattern - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByModelClustering: Holds the value of ByModelClustering.NOISE_ID.
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
NOLOG_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeFactory: Parameter for nolog
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_SPATIAL_DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier: Parameter to specify the non spatial distance function to use
NONBREAKING_SPACE - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Non-breaking unicode space character.
NonFlatRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends AbstractRTreeSettings> - 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.
NoParameterValueException - Exception in de.lmu.ifi.dbs.elki.utilities.optionhandling: Thrown by OptionHandler in case of incorrect parameter-array.
NoParameterValueException(String) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.optionhandling.NoParameterValueException: Thrown by OptionHandler in case of incorrect parameter-array.
NoParameterValueException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.optionhandling.NoParameterValueException: Thrown by OptionHandler in case of incorrect parameter-array.
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.algorithm.clustering.em.DiagonalGaussianModel: Normalization factor.
norm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel: Normalization factor.
norm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.SphericalGaussianModel: Normalization factor.
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.LorentzianDistanceFunction
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(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.
norm1() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: One norm
norm2() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Two norm
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.
normalizationRestore(O) - Method in class de.lmu.ifi.dbs.elki.result.textwriter.TextWriterStream: Restore a vector undoing any normalization that was applied.
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() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector: Normalizes this vector to the length of 1.0.
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
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: Normalization flag.
normalizeColumns() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Normalizes the columns of this matrix to length of 1.0.
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 Nguyen, X.
normalizeEigenPair(EigenPair) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.NormalizingEigenPairFilter: Normalizes an eigenpair consisting of eigenvector v and eigenvalue e s.t.
normalizeEquals(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: Normalizes v1 to the length of 1.0.
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
normalizeValue(double) - Method in class de.lmu.ifi.dbs.elki.math.MeanVariance: Return the normalized value (centered at the mean, distance normalized by standard deviation)
NormalizingEigenPairFilter - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca: The NormalizingEigenPairFilter normalizes all eigenvectors s.t.
NormalizingEigenPairFilter() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.NormalizingEigenPairFilter: Constructor.
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[
normDistrFactor - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel: Normalization factor.
normDistrFactor - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel: Normalization factor.
normDistrFactor - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.SphericalGaussianModel: Normalization factor.
normF() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Frobenius norm
normInf() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Infinity 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.FormatUtil: Preallocated exceptions.
NOT_FROM_ONE_CLUSTER_PROBABILITY - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.LMCLUS: Epsilon
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.
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.utilities.scaling.outlier.OutlierLinearScaling: 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.
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.
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.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).
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.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 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 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.BitsUtil: Find the number of leading zeros.
numberOfLeadingZeros(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.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.BitsUtil: Find the number of leading zeros.
numberOfLeadingZerosSigned(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.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.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.
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.BitsUtil: Find the number of trailing zeros.
numberOfTrailingZeros(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the number of trailing zeros.
numberOfTrailingZeros(int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the number of trailing zeros.
numberOfTrailingZerosSigned(long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the number of trailing zeros.
numberOfTrailingZerosSigned(long) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: Find the number of trailing zeros.
NumberParameter<THIS extends NumberParameter<THIS,T>,T extends 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(NumberVector) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil: Get the static instance.
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
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.
numNodes() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree: Determines and returns the number of nodes in this index.
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.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.
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.


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