A-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

A

a - Variable in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel: Model parameters: major and minor radius.
a - Variable in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D.Triangle: References to points in Delaunay2D.points
A0 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Constants for fast rational approximations.
A0 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator: Polynomial approximation
A0 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator: Polynomial approximation
A1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaLMMEstimator: Coefficients for polynomial approximation
A1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Constants for fast rational approximations.
A1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator: Polynomial approximation
A1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator: Polynomial approximation
A2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaLMMEstimator: Coefficients for polynomial approximation
A2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Constants for fast rational approximations.
A2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator: Polynomial approximation
A2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator: Polynomial approximation
A2Noncentral(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.AndersonDarlingTest: Test a sorted but not standardized data set.
A2StandardNormal(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.tests.AndersonDarlingTest: Test a sorted data set against the standard normal distribution.
A3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaLMMEstimator: Coefficients for polynomial approximation
A3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Constants for fast rational approximations.
A3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator: Polynomial approximation
A3 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator: Polynomial approximation
A4 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator: Constants for fast rational approximations.
ab - Variable in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D.Triangle: References to neighbor triangles
ABOD<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased: Angle-Based Outlier Detection / Angle-Based Outlier Factor.
ABOD(SimilarityFunction<? super V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD: Constructor for Angle-Based Outlier Detection (ABOD).
ABOD.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased: Parameterization class.
ABOD.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased.ABOD.Parameterizer
AbortException - Exception in de.lmu.ifi.dbs.elki.utilities.exceptions: Exception for aborting some process and transporting a message.
AbortException(String) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException: Exception for aborting some process and transporting a message.
AbortException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException: Exception for aborting some process and transporting a message.
absolute - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings: Use absolute variance, not relative variance.
absolute - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter: Indicates whether delta is an absolute or a relative value.
absolute - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter.Parameterizer: Indicates whether delta is an absolute or a relative value.
AbsolutePearsonCorrelationDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Absolute Pearson correlation distance function for feature vectors.
AbsolutePearsonCorrelationDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsolutePearsonCorrelationDistanceFunction: Deprecated.
Use static instance!
AbsolutePearsonCorrelationDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Parameterization class.
AbsolutePearsonCorrelationDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsolutePearsonCorrelationDistanceFunction.Parameterizer
AbsoluteUncenteredCorrelationDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Absolute uncentered correlation distance function for feature vectors.
AbsoluteUncenteredCorrelationDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsoluteUncenteredCorrelationDistanceFunction: Deprecated.
Use static instance!
AbsoluteUncenteredCorrelationDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Parameterization class.
AbsoluteUncenteredCorrelationDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsoluteUncenteredCorrelationDistanceFunction.Parameterizer
AbstractAggarwalYuOutlier<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Abstract base class for the sparse-grid-cell based outlier detection of Aggarwal and Yu.
AbstractAggarwalYuOutlier(int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier: Constructor.
AbstractAggarwalYuOutlier.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Parameterization class.
AbstractAggarwalYuOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier.Parameterizer
AbstractAlgorithm<R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm: This class serves also as a model of implementing an algorithm within this framework.
AbstractAlgorithm() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm: Constructor.
AbstractApplication - Class in de.lmu.ifi.dbs.elki.application: AbstractApplication sets the values for flags verbose and help.
AbstractApplication() - Constructor for class de.lmu.ifi.dbs.elki.application.AbstractApplication: Constructor.
AbstractApplication.Parameterizer - Class in de.lmu.ifi.dbs.elki.application: Parameterization class.
AbstractApplication.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.AbstractApplication.Parameterizer
AbstractBiclustering<V extends NumberVector,M extends BiclusterModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering: Abstract class as a convenience for different biclustering approaches.
AbstractBiclustering() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering: Constructor.
AbstractBulkSplit - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk: Encapsulates the required parameters for a bulk split of a spatial index.
AbstractBulkSplit() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk.AbstractBulkSplit: Constructor
AbstractClassifier<O,R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm.classification: Abstract base class for algorithms.
AbstractClassifier() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.classification.AbstractClassifier
AbstractConversionFilter<I,O> - Class in de.lmu.ifi.dbs.elki.datasource.filter: Abstract base class for simple conversion filters such as normalizations and projections.
AbstractConversionFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.AbstractConversionFilter
AbstractCovarianceMatrixBuilder - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca: Abstract class with the task of computing a Covariance matrix to be used in PCA.
AbstractCovarianceMatrixBuilder() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.AbstractCovarianceMatrixBuilder
AbstractCoverTree<O> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree: Abstract base class for cover tree variants.
AbstractCoverTree(Relation<O>, DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Constructor.
AbstractCoverTree.Factory<O,I extends AbstractCoverTree<O>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree: Index factory.
AbstractCoverTree.Factory(DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory: Constructor.
AbstractCoverTree.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree: Parameterization class.
AbstractCoverTree.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer
AbstractDatabase - Class in de.lmu.ifi.dbs.elki.database: Abstract base class for database API implementations.
AbstractDatabase() - Constructor for class de.lmu.ifi.dbs.elki.database.AbstractDatabase: Constructor.
AbstractDatabase.Parameterizer - Class in de.lmu.ifi.dbs.elki.database: Parameterization class.
AbstractDatabase.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.database.AbstractDatabase.Parameterizer
AbstractDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource: Abstract super class for all database connections.
AbstractDatabaseConnection(List<ObjectFilter>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.AbstractDatabaseConnection: Constructor.
AbstractDatabaseConnection.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource: Parameterization class.
AbstractDatabaseConnection.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.AbstractDatabaseConnection.Parameterizer
AbstractDatabaseDistanceFunction<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract super class for distance functions needing a database context.
AbstractDatabaseDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDatabaseDistanceFunction: Constructor.
AbstractDatabaseDistanceFunction.Instance<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: The actual instance bound to a particular database.
AbstractDatabaseDistanceFunction.Instance(Relation<O>, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDatabaseDistanceFunction.Instance: Constructor.
AbstractDatabaseDistanceQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.distance: Run a database query in a database context.
AbstractDatabaseDistanceQuery(Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDatabaseDistanceQuery: Constructor.
AbstractDBIDRangeDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract base class for distance functions that rely on integer offsets within a consecutive range.
AbstractDBIDRangeDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDBIDRangeDistanceFunction
AbstractDBIDSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: Abstract super class for distance functions needing a preprocessor.
AbstractDBIDSimilarityFunction(Relation<? extends DBID>) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractDBIDSimilarityFunction: Constructor.
AbstractDBIDSimilarityQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.similarity: Run a database query in a database context.
AbstractDBIDSimilarityQuery(Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.similarity.AbstractDBIDSimilarityQuery: Constructor.
AbstractDBOutlier<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Simple distance based outlier detection algorithms.
AbstractDBOutlier(DistanceFunction<? super O>, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier: Constructor with actual parameters.
AbstractDBOutlier.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Parameterization class.
AbstractDBOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier.Parameterizer
AbstractDependenceMeasure - Class in de.lmu.ifi.dbs.elki.math.statistics.dependence: Abstract base class for dependence measures.
AbstractDependenceMeasure() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
AbstractDimensionsSelectingDistanceFunction<V extends FeatureVector<?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace: Abstract base class for distances computed only in subspaces.
AbstractDimensionsSelectingDistanceFunction(long[]) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction: Constructor.
AbstractDimensionsSelectingDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace: Parameterization class.
AbstractDimensionsSelectingDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction.Parameterizer
AbstractDirectoryEntry - Class in de.lmu.ifi.dbs.elki.index.tree: Abstract superclass for entries in an tree based index structure.
AbstractDirectoryEntry() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractDirectoryEntry: Empty constructor for serialization purposes.
AbstractDirectoryEntry(Integer) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractDirectoryEntry: Constructor.
AbstractDiscreteUncertainifier<UO extends UncertainObject> - Class in de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier: Factory class for discrete uncertain objects.
AbstractDiscreteUncertainifier(Uncertainifier<?>, int, int) - Constructor for class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier: Constructor.
AbstractDiscreteUncertainifier.Parameterizer - Class in de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier: Parameterizer.
AbstractDiscreteUncertainifier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Parameterizer
AbstractDistanceBasedAlgorithm<O,R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm: Abstract base class for distance-based algorithms.
AbstractDistanceBasedAlgorithm(DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm: Constructor.
AbstractDistanceBasedAlgorithm.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm: Parameterization helper class.
AbstractDistanceBasedAlgorithm.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm.Parameterizer
AbstractDistanceBasedSpatialOutlier<N,O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial: Abstract base class for distance-based spatial outlier detection methods.
AbstractDistanceBasedSpatialOutlier(NeighborSetPredicate.Factory<N>, DistanceFunction<O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier: Constructor.
AbstractDistanceBasedSpatialOutlier.Parameterizer<N,O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial: Parameterization class.
AbstractDistanceBasedSpatialOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier.Parameterizer
AbstractDistanceKNNQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.knn: Instance for the query on a particular database.
AbstractDistanceKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.knn.AbstractDistanceKNNQuery: Constructor.
AbstractDistanceQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.distance: A distance query serves as adapter layer for database and primitive distances.
AbstractDistanceQuery(Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDistanceQuery: Constructor.
AbstractDistanceRangeQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.range: Abstract base class for range queries that use a distance query in their instance
AbstractDistanceRangeQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.range.AbstractDistanceRangeQuery: Constructor.
AbstractDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution: Abstract base class for distributions.
AbstractDistribution(RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.AbstractDistribution: Constructor.
AbstractDistribution(Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.AbstractDistribution: Constructor.
AbstractDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution: Parameterization class.
AbstractDistribution.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.AbstractDistribution.Parameterizer
AbstractDoubleProcessor - Class in de.lmu.ifi.dbs.elki.parallel.processor: Abstract base class for processors that output double values.
AbstractDoubleProcessor() - Constructor for class de.lmu.ifi.dbs.elki.parallel.processor.AbstractDoubleProcessor
AbstractDoubleProcessor.Instance - Class in de.lmu.ifi.dbs.elki.parallel.processor: Instance.
AbstractDoubleProcessor.Instance(SharedDouble.Instance) - Constructor for class de.lmu.ifi.dbs.elki.parallel.processor.AbstractDoubleProcessor.Instance: Constructor.
AbstractEarthModel - Class in de.lmu.ifi.dbs.elki.math.geodesy: Abstract base class for earth models with shared glue code.
AbstractEarthModel(double, double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel: Constructor.
AbstractEditDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Edit Distance for FeatureVectors.
AbstractEditDistanceFunction(double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction: Constructor.
AbstractEditDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Parameterization class.
AbstractEditDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction.Parameterizer
AbstractEMModelFactory<V extends NumberVector,M extends MeanModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em: Abstract base class for initializing EM.
AbstractEMModelFactory(KMeansInitialization<V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.AbstractEMModelFactory: Constructor.
AbstractEMModelFactory.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em: Parameterization class.
AbstractEMModelFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.AbstractEMModelFactory.Parameterizer
AbstractExpMADEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for estimators based on the median and MAD.
AbstractExpMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator: Constructor.
AbstractExternalizablePage - Class in de.lmu.ifi.dbs.elki.persistent: Abstract superclass for pages.
AbstractExternalizablePage() - Constructor for class de.lmu.ifi.dbs.elki.persistent.AbstractExternalizablePage: Empty constructor for Externalizable interface.
AbstractFilteredPCAIndex<NV extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca: Abstract base class for a local PCA based index.
AbstractFilteredPCAIndex(Relation<NV>, PCAFilteredRunner) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex: Constructor.
AbstractFilteredPCAIndex.Factory<NV extends NumberVector,I extends AbstractFilteredPCAIndex<NV>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca: Factory class.
AbstractFilteredPCAIndex.Factory(DistanceFunction<NV>, PCAFilteredRunner) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex.Factory: Constructor.
AbstractFilteredPCAIndex.Factory.Parameterizer<NV extends NumberVector,I extends AbstractFilteredPCAIndex<NV>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.localpca: Parameterization class.
AbstractFilteredPCAIndex.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.AbstractFilteredPCAIndex.Factory.Parameterizer
AbstractFrequentItemsetAlgorithm - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining: Abstract base class for frequent itemset mining.
AbstractFrequentItemsetAlgorithm(double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.AbstractFrequentItemsetAlgorithm: Constructor.
AbstractFrequentItemsetAlgorithm(double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.AbstractFrequentItemsetAlgorithm: Constructor.
AbstractFrequentItemsetAlgorithm.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining: Parameterization class.
AbstractFrequentItemsetAlgorithm.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.AbstractFrequentItemsetAlgorithm.Parameterizer
AbstractFullProjection - Class in de.lmu.ifi.dbs.elki.visualization.projections: Abstract base class for full projections.
AbstractFullProjection(Projector, LinearScale[]) - Constructor for class de.lmu.ifi.dbs.elki.visualization.projections.AbstractFullProjection: Constructor.
AbstractHDBSCAN<O,R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Abstract base class for HDBSCAN variations.
AbstractHDBSCAN(DistanceFunction<? super O>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN: Constructor.
AbstractHDBSCAN.HDBSCANAdapter - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Class for processing the HDBSCAN G_mpts graph.
AbstractHDBSCAN.HDBSCANAdapter(ArrayDBIDs, DoubleDataStore, DistanceQuery<?>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HDBSCANAdapter: Constructor.
AbstractHDBSCAN.HeapMSTCollector - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Class for collecting the minimum spanning tree edges into a heap.
AbstractHDBSCAN.HeapMSTCollector(DoubleLongHeap, FiniteProgress, Logging) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HeapMSTCollector: Constructor.
AbstractHDBSCAN.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Parameterization class
AbstractHDBSCAN.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.Parameterizer
AbstractHierarchicalResult - Class in de.lmu.ifi.dbs.elki.result: Abstract class for a result object with hierarchy
AbstractHierarchicalResult() - Constructor for class de.lmu.ifi.dbs.elki.result.AbstractHierarchicalResult: Constructor.
AbstractHistogramVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram: One-dimensional projected visualization.
AbstractHistogramVisualization(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.AbstractHistogramVisualization: Constructor.
AbstractHoldout - Class in de.lmu.ifi.dbs.elki.evaluation.classification.holdout: Split a data set for holdout evaluation.
AbstractHoldout() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.AbstractHoldout
AbstractIndex<O> - Class in de.lmu.ifi.dbs.elki.index: Abstract base class for indexes with some implementation defaults.
AbstractIndex(Relation<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.AbstractIndex: Constructor.
AbstractIndexBasedDistanceFunction<O,I extends Index> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract super class for distance functions needing a database index.
AbstractIndexBasedDistanceFunction(IndexFactory<O, I>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractIndexBasedDistanceFunction: Constructor.
AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,F extends DistanceFunction<? super O>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: The actual instance bound to a particular database.
AbstractIndexBasedDistanceFunction.Instance(Relation<O>, I, F) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractIndexBasedDistanceFunction.Instance: Constructor.
AbstractIndexBasedDistanceFunction.Parameterizer<F extends IndexFactory<?,?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Parameterization class.
AbstractIndexBasedDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractIndexBasedDistanceFunction.Parameterizer
AbstractIndexBasedSimilarityFunction<O,I extends Index> - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: Abstract super class for distance functions needing a preprocessor.
AbstractIndexBasedSimilarityFunction(IndexFactory<O, I>) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractIndexBasedSimilarityFunction: Constructor.
AbstractIndexBasedSimilarityFunction.Instance<O,I extends Index> - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: The actual instance bound to a particular database.
AbstractIndexBasedSimilarityFunction.Instance(Relation<O>, I) - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractIndexBasedSimilarityFunction.Instance: Constructor.
AbstractIndexBasedSimilarityFunction.Parameterizer<F extends IndexFactory<?,?>> - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: Parameterization class.
AbstractIndexBasedSimilarityFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractIndexBasedSimilarityFunction.Parameterizer
AbstractIntegerDBIDFactory - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Abstract base class for DBID factories.
AbstractIntegerDBIDFactory() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
AbstractIntrinsicDimensionalityEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality: Abstract base class for ID estimators.
AbstractIntrinsicDimensionalityEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator
AbstractKMeans<V extends NumberVector,M extends Model> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans: Abstract base class for k-means implementations.
AbstractKMeans(NumberVectorDistanceFunction<? super V>, int, int, KMeansInitialization<? super V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans: Constructor.
AbstractKMeans.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans: Parameterization class.
AbstractKMeans.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Parameterizer
AbstractKMeansInitialization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization: Abstract base class for common k-means initializations.
AbstractKMeansInitialization(RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization: Constructor.
AbstractKMeansInitialization.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization: Parameterization class.
AbstractKMeansInitialization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.AbstractKMeansInitialization.Parameterizer
AbstractKMeansQualityMeasure<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality: Base class for evaluating clusterings by information criteria (such as AIC or BIC).
AbstractKMeansQualityMeasure() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.AbstractKMeansQualityMeasure
AbstractLeafEntry - Class in de.lmu.ifi.dbs.elki.index.tree: Abstract superclass for entries in an tree based index structure.
AbstractLeafEntry() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractLeafEntry: Empty constructor for serialization purposes.
AbstractLeafEntry(DBID) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractLeafEntry: Constructor.
AbstractLMMEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for L-Moments based estimators (LMM).
AbstractLMMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLMMEstimator: Constructor.
AbstractLogMADEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for estimators based on the median and MAD.
AbstractLogMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator: Constructor.
AbstractLogMeanVarianceEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Estimators that work on Mean and Variance only (i.e. the first two moments only).
AbstractLogMeanVarianceEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator: Constructor.
AbstractLogMOMEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for estimators based on the statistical moments.
AbstractLogMOMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMOMEstimator: Constructor.
AbstractMADEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for estimators based on the median and MAD.
AbstractMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator: Constructor.
AbstractMaterializeKNNPreprocessor<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn: Abstract base class for KNN Preprocessors.
AbstractMaterializeKNNPreprocessor(Relation<O>, DistanceFunction<? super O>, int) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor: Constructor.
AbstractMaterializeKNNPreprocessor.Factory<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn: The parameterizable factory.
AbstractMaterializeKNNPreprocessor.Factory(int, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory: Index factory.
AbstractMaterializeKNNPreprocessor.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.knn: Parameterization class.
AbstractMaterializeKNNPreprocessor.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory.Parameterizer
AbstractMeanVarianceEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Estimators that work on Mean and Variance only (i.e. the first two moments only).
AbstractMeanVarianceEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator: Constructor.
AbstractMkTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees: Abstract class for all M-Tree variants supporting processing of reverse k-nearest neighbor queries by using the k-nn distances of the entries, where k is less than or equal to the given parameter.
AbstractMkTree(Relation<O>, PageFile<N>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree: Constructor.
AbstractMkTreeUnified<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MkTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees: Abstract class for all M-Tree variants supporting processing of reverse k-nearest neighbor queries by using the k-nn distances of the entries, where k is less than or equal to the given parameter.
AbstractMkTreeUnified(Relation<O>, PageFile<N>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTreeUnified: Constructor.
AbstractMkTreeUnifiedFactory<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,I extends AbstractMkTree<O,N,E,S> & Index,S extends MkTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees: Abstract factory for various Mk-Trees
AbstractMkTreeUnifiedFactory(PageFileFactory<?>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTreeUnifiedFactory: Constructor.
AbstractMkTreeUnifiedFactory.Parameterizer<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MkTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees: Parameterization class.
AbstractMkTreeUnifiedFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTreeUnifiedFactory.Parameterizer
AbstractModel - Class in de.lmu.ifi.dbs.elki.data.model: Abstract base class for Cluster Models.
AbstractModel() - Constructor for class de.lmu.ifi.dbs.elki.data.model.AbstractModel
AbstractMOMEstimator<D extends Distribution> - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Abstract base class for estimators based on the statistical moments.
AbstractMOMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMOMEstimator: Constructor.
AbstractMTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: Abstract super class for all M-Tree variants.
AbstractMTree(PageFile<N>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree: Constructor.
AbstractMTree.Statistics - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: Class for tracking some statistics.
AbstractMTree.Statistics() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree.Statistics: Constructor.
AbstractMTreeFactory<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,I extends AbstractMTree<O,N,E,S> & Index,S extends MTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: Abstract factory for various MTrees
AbstractMTreeFactory(PageFileFactory<?>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeFactory: Constructor.
AbstractMTreeFactory.Parameterizer<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: Parameterization class.
AbstractMTreeFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeFactory.Parameterizer
AbstractMTreeNode<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: Abstract super class for nodes in M-Tree variants.
AbstractMTreeNode() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode: Empty constructor for Externalizable interface.
AbstractMTreeNode(int, boolean, Class<? super E>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode: Creates a new MTreeNode with the specified parameters.
AbstractNeighborhoodOutlier<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial: Abstract base class for spatial outlier detection methods using a spatial neighborhood.
AbstractNeighborhoodOutlier(NeighborSetPredicate.Factory<O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier: Constructor
AbstractNeighborhoodOutlier.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial: Parameterization class.
AbstractNeighborhoodOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier.Parameterizer
AbstractNode<E extends Entry> - Class in de.lmu.ifi.dbs.elki.index.tree: Abstract superclass for nodes in an tree based index structure.
AbstractNode() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Empty constructor for Externalizable interface.
AbstractNode(int, boolean, Class<? super E>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Creates a new Node with the specified parameters.
AbstractNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization: Abstract super class for all normalizations.
AbstractNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.AbstractNormalization: Initializes the option handler and the parameter map.
AbstractNumberConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints: Abstract super class for constraints dealing with a certain number value.
AbstractNumberConstraint(Number) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.AbstractNumberConstraint: Creates an abstract number constraint.
AbstractNumberVector - Class in de.lmu.ifi.dbs.elki.data: AbstractNumberVector is an abstract implementation of FeatureVector.
AbstractNumberVector() - Constructor for class de.lmu.ifi.dbs.elki.data.AbstractNumberVector
AbstractNumberVector.Factory<V extends AbstractNumberVector> - Class in de.lmu.ifi.dbs.elki.data: Factory class.
AbstractNumberVector.Factory() - Constructor for class de.lmu.ifi.dbs.elki.data.AbstractNumberVector.Factory
AbstractNumberVectorDistanceBasedAlgorithm<O,R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm: Abstract base class for distance-based algorithms that need to work with synthetic numerical vectors such as mean vectors.
AbstractNumberVectorDistanceBasedAlgorithm(NumberVectorDistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm: Constructor.
AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm: Parameterization helper class.
AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer
AbstractNumberVectorDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract base class for the most common family of distance functions: defined on number vectors and returning double values.
AbstractNumberVectorDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction: Constructor.
AbstractNumberVectorNorm - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract base class for double-valued number-vector-based distances based on norms.
AbstractNumberVectorNorm() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorNorm
AbstractObjDynamicHistogram<T> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: A dynamic histogram can dynamically adapt the number of bins to the data fed into the histogram.
AbstractObjDynamicHistogram(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Constructor.
AbstractObjStaticHistogram<T> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Histogram class storing double values.
AbstractObjStaticHistogram(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjStaticHistogram: Constructor.
AbstractObjStaticHistogram.Iter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Iterator class.
AbstractObjStaticHistogram.Iter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjStaticHistogram.Iter
AbstractOPTICS<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: The OPTICS algorithm for density-based hierarchical clustering.
AbstractOPTICS(DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS: Constructor.
AbstractOPTICS.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: Parameterization class.
AbstractOPTICS.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS.Parameterizer
AbstractOPTICSVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.optics: Abstract base class for OPTICS visualizer
AbstractOPTICSVisualization(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.AbstractOPTICSVisualization: Constructor.
AbstractPageFile - Class in de.lmu.ifi.dbs.elki.persistent: Abstract base class for the page file API for both caches and true page files (in-memory and on-disk).
AbstractPageFile() - Constructor for class de.lmu.ifi.dbs.elki.persistent.AbstractPageFile: Constructor.
AbstractPageFileFactory - Class in de.lmu.ifi.dbs.elki.persistent: Abstract page file factory.
AbstractPageFileFactory(int) - Constructor for class de.lmu.ifi.dbs.elki.persistent.AbstractPageFileFactory: Constructor.
AbstractPageFileFactory.Parameterizer - Class in de.lmu.ifi.dbs.elki.persistent: Parameterization class.
AbstractPageFileFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.persistent.AbstractPageFileFactory.Parameterizer
AbstractParallelVisualization<NV> - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Abstract base class for parallel visualizations.
AbstractParallelVisualization(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AbstractParallelVisualization: Constructor.
AbstractParameter<THIS extends AbstractParameter<THIS,T>,T> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters: Abstract class for specifying a parameter.
AbstractParameter(OptionID, T) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter: Constructs a parameter with the given optionID, constraints, and default value.
AbstractParameter(OptionID, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter: Constructs a parameter with the given optionID, constraints, and optional flag.
AbstractParameter(OptionID) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter: Constructs a parameter with the given optionID, and constraints.
AbstractParameterConfigurator<T extends Parameter<?>> - Class in de.lmu.ifi.dbs.elki.gui.configurator: Abstract class to produce a configurator for a particular parameter.
AbstractParameterConfigurator(T, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.AbstractParameterConfigurator: Constructor.
AbstractParameterization - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization: Abstract class with shared code for parameterization handling.
AbstractParameterization() - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.AbstractParameterization
AbstractParameterizer - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling: Abstract base class that handles the parameterization of a class.
AbstractParameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer
AbstractPartialReinsert - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert: Abstract base class for reinsertion strategies that have a "relative amount" parameter to partially reinsert entries.
AbstractPartialReinsert(double, SpatialPrimitiveDistanceFunction<?>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.AbstractPartialReinsert: Constructor.
AbstractPartialReinsert.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert: Parameterization class.
AbstractPartialReinsert.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.AbstractPartialReinsert.Parameterizer
AbstractPrecomputedNeighborhood - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood: Abstract base class for precomputed neighborhoods.
AbstractPrecomputedNeighborhood(DataStore<DBIDs>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.AbstractPrecomputedNeighborhood: Constructor.
AbstractPrecomputedNeighborhood.Factory<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood: Factory class.
AbstractPrecomputedNeighborhood.Factory() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.AbstractPrecomputedNeighborhood.Factory
AbstractPreferenceVectorIndex<NV extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Abstract base class for preference vector based algorithms.
AbstractPreferenceVectorIndex(Relation<NV>) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.preference.AbstractPreferenceVectorIndex: Constructor.
AbstractPreferenceVectorIndex.Factory<V extends NumberVector,I extends PreferenceVectorIndex<V>> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Factory class.
AbstractPreferenceVectorIndex.Factory() - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.preference.AbstractPreferenceVectorIndex.Factory
AbstractPreprocessorIndex<O,R> - Class in de.lmu.ifi.dbs.elki.index.preprocessed: Abstract base class for simple preprocessor based indexes, requiring a simple object storage for preprocessing results.
AbstractPreprocessorIndex(Relation<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.AbstractPreprocessorIndex: Constructor.
AbstractPrimitiveDistanceBasedAlgorithm<O,R extends Result> - Class in de.lmu.ifi.dbs.elki.algorithm: Abstract base class for distance-based algorithms that need to work with synthetic objects such as mean vectors.
AbstractPrimitiveDistanceBasedAlgorithm(PrimitiveDistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractPrimitiveDistanceBasedAlgorithm: Constructor.
AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm: Parameterization helper class.
AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer
AbstractPrimitiveDistanceFunction<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: AbstractDistanceFunction provides some methods valid for any extending class.
AbstractPrimitiveDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction: Constructor.
AbstractPrimitiveSimilarityFunction<O> - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: Base implementation of a similarity function.
AbstractPrimitiveSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractPrimitiveSimilarityFunction: Constructor.
AbstractProgress - Class in de.lmu.ifi.dbs.elki.logging.progress: Abstract base class for FiniteProgress objects.
AbstractProgress(String) - Constructor for class de.lmu.ifi.dbs.elki.logging.progress.AbstractProgress: Default constructor.
AbstractProjectedClustering<R extends Clustering<?>,V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Abstract superclass for projected clustering algorithms, like PROCLUS and ORCLUS.
AbstractProjectedClustering(int, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering: Internal constructor.
AbstractProjectedClustering.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Parameterization class.
AbstractProjectedClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering.Parameterizer
AbstractProjectedHashFunctionFamily - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies: Abstract base class for projection based hash functions.
AbstractProjectedHashFunctionFamily(RandomFactory, RandomProjectionFamily, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.AbstractProjectedHashFunctionFamily: Constructor.
AbstractProjectedHashFunctionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies: Parameterization class.
AbstractProjectedHashFunctionFamily.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.AbstractProjectedHashFunctionFamily.Parameterizer
AbstractProjection - Class in de.lmu.ifi.dbs.elki.visualization.projections: Abstract base projection class.
AbstractProjection(Projector, LinearScale[]) - Constructor for class de.lmu.ifi.dbs.elki.visualization.projections.AbstractProjection: Constructor.
AbstractRandomProjectionFamily - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Abstract base class for random projection families.
AbstractRandomProjectionFamily(RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.AbstractRandomProjectionFamily: Constructor.
AbstractRandomProjectionFamily.MatrixProjection - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Class to project using a matrix multiplication.
AbstractRandomProjectionFamily.MatrixProjection(double[][]) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.AbstractRandomProjectionFamily.MatrixProjection: Constructor.
AbstractRandomProjectionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Parameterization interface (with the shared parameters)
AbstractRandomProjectionFamily.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.AbstractRandomProjectionFamily.Parameterizer
AbstractRangeQueryNeighborPredicate<O,M> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: Abstract local model neighborhood predicate.
AbstractRangeQueryNeighborPredicate(double, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate: Full constructor.
AbstractRangeQueryNeighborPredicate.Instance<N,M> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: Instance for a particular data set.
AbstractRangeQueryNeighborPredicate.Instance(DBIDs, DataStore<M>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Instance: Constructor.
AbstractRangeQueryNeighborPredicate.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: Parameterization class
AbstractRangeQueryNeighborPredicate.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer
AbstractRefiningIndex<O> - Class in de.lmu.ifi.dbs.elki.index: Abstract base class for Filter-refinement indexes.
AbstractRefiningIndex(Relation<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex: Constructor.
AbstractRefiningIndex.AbstractKNNQuery - Class in de.lmu.ifi.dbs.elki.index: KNN query for this index.
AbstractRefiningIndex.AbstractKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex.AbstractKNNQuery: Constructor.
AbstractRefiningIndex.AbstractRangeQuery - Class in de.lmu.ifi.dbs.elki.index: Range query for this index.
AbstractRefiningIndex.AbstractRangeQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex.AbstractRangeQuery: Constructor.
AbstractRelation<O> - Class in de.lmu.ifi.dbs.elki.database.relation: Abstract base class for relations.
AbstractRelation() - Constructor for class de.lmu.ifi.dbs.elki.database.relation.AbstractRelation: Constructor.
AbstractRKNNQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.rknn: Instance for the query on a particular database.
AbstractRKNNQuery(DistanceQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.rknn.AbstractRKNNQuery: Constructor.
AbstractRStarTree<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 index structures based on a R*-Tree.
AbstractRStarTree(PageFile<N>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree: Constructor.
AbstractRStarTree.Statistics - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: Class for tracking some statistics.
AbstractRStarTree.Statistics() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree.Statistics: Constructor.
AbstractRStarTreeFactory<O extends NumberVector,N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,I extends AbstractRStarTree<N,E,S> & Index,S extends AbstractRTreeSettings> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: Abstract factory for R*-Tree based trees.
AbstractRStarTreeFactory(PageFileFactory<?>, S) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeFactory: Constructor.
AbstractRStarTreeFactory.Parameterizer<O extends NumberVector,S extends AbstractRTreeSettings> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: Parameterization class.
AbstractRStarTreeFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeFactory.Parameterizer
AbstractRStarTreeNode<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: Abstract superclass for nodes in a R*-Tree.
AbstractRStarTreeNode() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode: Empty constructor for Externalizable interface.
AbstractRStarTreeNode(int, boolean, Class<? super E>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode: Creates a new AbstractRStarTreeNode with the specified parameters.
AbstractRTreeSettings - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: Class to wrap common Rtree settings.
AbstractRTreeSettings() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRTreeSettings
AbstractScatterplotVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot: Default class to handle 2D projected visualizations.
AbstractScatterplotVisualization(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AbstractScatterplotVisualization: Constructor.
AbstractScoreEvaluation - Class in de.lmu.ifi.dbs.elki.evaluation.scores: Abstract base class for evaluating a scoring result.
AbstractScoreEvaluation() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation
AbstractSetDistanceFunction<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.set: Abstract base class for set distance functions.
AbstractSetDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.set.AbstractSetDistanceFunction
AbstractSimilarityAdapter<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Adapter from a similarity function to a distance function.
AbstractSimilarityAdapter(SimilarityFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter: Constructor.
AbstractSimilarityAdapter.Instance<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Inner proxy class for SNN distance function.
AbstractSimilarityAdapter.Instance(Relation<O>, DistanceFunction<? super O>, SimilarityQuery<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter.Instance: Constructor.
AbstractSimilarityAdapter.Parameterizer<O,S extends SimilarityFunction<? super O>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Parameterization class.
AbstractSimilarityAdapter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter.Parameterizer
AbstractSimilarityQuery<O> - Class in de.lmu.ifi.dbs.elki.database.query.similarity: A distance query serves as adapter layer for database and primitive similarity functions.
AbstractSimilarityQuery(Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.database.query.similarity.AbstractSimilarityQuery: Constructor.
AbstractSimpleProjection - Class in de.lmu.ifi.dbs.elki.visualization.projections: Abstract base class for "simple" projections.
AbstractSimpleProjection(Projector, LinearScale[]) - Constructor for class de.lmu.ifi.dbs.elki.visualization.projections.AbstractSimpleProjection: Constructor.
AbstractSingleParameterConfigurator<T extends Parameter<?>> - Class in de.lmu.ifi.dbs.elki.gui.configurator: Base class for MiniGUI input helpers
AbstractSingleParameterConfigurator(T, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.AbstractSingleParameterConfigurator: Constructor.
AbstractSpatialDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract base class for typical distance functions that allow rectangle-to-rectangle lower bounds.
AbstractSpatialDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialDistanceFunction
AbstractSpatialNorm - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Abstract base class for typical distance functions that allow rectangle-to-rectangle lower bounds.
AbstractSpatialNorm() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractSpatialNorm
AbstractSpatialSorter - Class in de.lmu.ifi.dbs.elki.math.spacefillingcurves: Abstract base class for spatial sorters, offering shared functionality.
AbstractSpatialSorter() - Constructor for class de.lmu.ifi.dbs.elki.math.spacefillingcurves.AbstractSpatialSorter: Constructor.
AbstractStaticHistogram - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Abstract base class for histograms.
AbstractStaticHistogram(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractStaticHistogram: Histogram constructor
AbstractStaticHistogram.Iter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Iterator class to iterate over all bins.
AbstractStaticHistogram.Iter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractStaticHistogram.Iter
AbstractStatistic - Class in de.lmu.ifi.dbs.elki.logging.statistics: Abstract base class for statistics tracking.
AbstractStatistic(String) - Constructor for class de.lmu.ifi.dbs.elki.logging.statistics.AbstractStatistic: Constructor.
AbstractStoringPageFile - Class in de.lmu.ifi.dbs.elki.persistent: Abstract class implementing general methods of a PageFile.
AbstractStoringPageFile(int) - Constructor for class de.lmu.ifi.dbs.elki.persistent.AbstractStoringPageFile: Creates a new PageFile.
AbstractStreamConversionFilter<I,O> - Class in de.lmu.ifi.dbs.elki.datasource.filter: Abstract base class for simple conversion filters such as normalizations and projections.
AbstractStreamConversionFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamConversionFilter
AbstractStreamFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter: Abstract base class for streaming filters.
AbstractStreamFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamFilter
AbstractStreamingParser - Class in de.lmu.ifi.dbs.elki.datasource.parser: Base class for streaming parsers.
AbstractStreamingParser(CSVReaderFormat) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.AbstractStreamingParser: Constructor.
AbstractStreamingParser.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.parser: Parameterization class.
AbstractStreamingParser.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.AbstractStreamingParser.Parameterizer
AbstractStreamNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization: Abstract super class for all normalizations.
AbstractStreamNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.AbstractStreamNormalization: Initializes the option handler and the parameter map.
AbstractSupervisedProjectionVectorFilter<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform: Base class for supervised projection methods.
AbstractSupervisedProjectionVectorFilter(int) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.AbstractSupervisedProjectionVectorFilter: Constructor.
AbstractSupervisedProjectionVectorFilter.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.transform: Parameterization class.
AbstractSupervisedProjectionVectorFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.transform.AbstractSupervisedProjectionVectorFilter.Parameterizer
AbstractTooltipVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot: General base class for a tooltip visualizer.
AbstractTooltipVisualization(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AbstractTooltipVisualization: Constructor.
AbstractUncertainObject - Class in de.lmu.ifi.dbs.elki.data.uncertain: Abstract base implementation for UncertainObjects, providing shared functionality such as bounding box access and random generation.
AbstractUncertainObject() - Constructor for class de.lmu.ifi.dbs.elki.data.uncertain.AbstractUncertainObject
AbstractVectorConversionFilter<I,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter: Abstract class for filters that produce number vectors.
AbstractVectorConversionFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.AbstractVectorConversionFilter
AbstractVectorIter - Class in de.lmu.ifi.dbs.elki.evaluation.scores.adapter: Class to iterate over a number vector in decreasing order.
AbstractVectorIter(NumberVector) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.AbstractVectorIter: Constructor.
AbstractVectorSimilarityFunction - Class in de.lmu.ifi.dbs.elki.distance.similarityfunction: Abstract base class for double-valued primitive similarity functions.
AbstractVectorSimilarityFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractVectorSimilarityFunction
AbstractVectorStreamConversionFilter<I,O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter: Abstract base class for streaming filters that produce vectors.
AbstractVectorStreamConversionFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.AbstractVectorStreamConversionFilter
AbstractVisFactory - Class in de.lmu.ifi.dbs.elki.visualization.visualizers: Abstract superclass for Visualizers (aka: Visualization Factories).
AbstractVisFactory() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisFactory: Constructor.
AbstractVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers: Abstract base class for visualizations.
AbstractVisualization(VisualizationTask, VisualizationPlot, double, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisualization: Constructor.
acceptsType(SimpleTypeInformation<?>) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.CorePredicate: Test whether the neighborhood type T is accepted by this predicate.
acceptsType(SimpleTypeInformation<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.FourCCorePredicate
acceptsType(SimpleTypeInformation<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.MinPtsCorePredicate
acceptsType(SimpleTypeInformation<?>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.PreDeConCorePredicate
accumulateDataStoreEvents() - Method in class de.lmu.ifi.dbs.elki.database.AbstractDatabase
accumulateDataStoreEvents() - Method in interface de.lmu.ifi.dbs.elki.database.Database: Collects all insertion, deletion and update events until Database.flushDataStoreEvents() is called.
accumulateDataStoreEvents - Variable in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: Indicates whether DataStoreEvents should be accumulated and fired as one event on demand.
accumulateDataStoreEvents() - Method in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: Collects successive insertion, deletion or update events.
AchlioptasRandomProjectionFamily - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Random projections as suggested by Dimitris Achlioptas.
AchlioptasRandomProjectionFamily(double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.AchlioptasRandomProjectionFamily: Constructor.
AchlioptasRandomProjectionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Parameterization class.
AchlioptasRandomProjectionFamily.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.AchlioptasRandomProjectionFamily.Parameterizer
ACTION_CANCELED - Static variable in class de.lmu.ifi.dbs.elki.gui.util.TreePopup: Action string for canceled operations (escape button pressed).
ACTION_QUIT - Static variable in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI: Quit action, for mnemonics.
ACTION_SELECTED - Static variable in class de.lmu.ifi.dbs.elki.gui.util.TreePopup: Action string for confirmed operations (enter or click).
actionListeners - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot: Action listeners for this plot.
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassListParameterConfigurator: Callback to show the popup menu
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassParameterConfigurator
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.EnumParameterConfigurator
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.FileParameterConfigurator: Button callback to show the file selector
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.FlagParameterConfigurator
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.TextParameterConfigurator
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.ClassListEditor: Callback to show the popup menu
actionPerformed(ActionEvent) - Method in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.FileNameEditor: Button callback to show the file selector
activate() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.JSVGUpdateSynchronizer
activate() - Method in interface de.lmu.ifi.dbs.elki.visualization.svg.UpdateSynchronizer: This method is called whenever a new pending event was added.
activate() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuAction: Menu item was activated.
activate() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction.SetStyleAction
activate() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.SwitchModeAction
activate() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.SwitchStyleAction
active() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuToggle: Return the current state.
activeEditor - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.AdjustingEditor: We need to remember which editor we delegated to, so we know whom to ask for the value entered.
activeRatio - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer: Last ratio of the Canvas applied
actualMaximum - Variable in class de.lmu.ifi.dbs.elki.result.outlier.BasicOutlierScoreMeta: Store the actual maximum
actualMaximum - Variable in class de.lmu.ifi.dbs.elki.result.outlier.ProbabilisticOutlierScore: Actual maximum seen, if given by the algorithm.
actualMinimum - Variable in class de.lmu.ifi.dbs.elki.result.outlier.BasicOutlierScoreMeta: Store the actual minimum
actualMinimum - Variable in class de.lmu.ifi.dbs.elki.result.outlier.ProbabilisticOutlierScore: Actual minimum seen, if given by the algorithm.
actualPairs - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segments: Pairs actually present in the data set
adapatedStrongEigenvectors - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult: The diagonal matrix of adapted strong eigenvalues: eigenvectors * e_czech.
adapatedStrongEigenvectors() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult: Returns the adapted strong eigenvectors.
adaptedCoefficientOfDetermination() - Method in class de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression: Returns the adapted coefficient of determination
adapter - Variable in class de.lmu.ifi.dbs.elki.data.projection.FeatureSelection: Array adapter.
AdaptiveSortTileRecursiveBulkSplit - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk: This is variation of the original STR bulk load for non-rectangular data spaces.
AdaptiveSortTileRecursiveBulkSplit() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk.AdaptiveSortTileRecursiveBulkSplit
AdaptiveSortTileRecursiveBulkSplit.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk: Parameterization class.
AdaptiveSortTileRecursiveBulkSplit.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk.AdaptiveSortTileRecursiveBulkSplit.Parameterizer
add(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster: Add new objects to the cluster.
add(DBIDRef, double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.PointerHierarchyRepresentationBuilder: Add an element to the pointer representation.
add(DBIDRef, double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.ClusterOrder: Add an object to the cluster order.
add(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
add(double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList
add(DoubleDBIDPair) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList
add(double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDListKNNHeap
add(double, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList
add(DoubleDBIDPair) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList
add(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TroveHashSetModifiableDBIDs
add(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDBIDs: Add a single DBID to the collection.
add(double, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDoubleDBIDList: Add an object to this result.
add(DoubleDBIDPair) - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDoubleDBIDList: Add an element.
add(Vector) - Method in class de.lmu.ifi.dbs.elki.math.geometry.GrahamScanConvexHull2D: Add a single point to the list (this does not compute the hull!)
add(Vector) - Method in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D: Add a single point to the list (this does not compute or update the triangulation!)
add(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geometry.XYCurve: Add a coordinate pair, but don't simplify
add(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve: Add a coordinate pair, but don't simplify
add(Result, Result) - Method in class de.lmu.ifi.dbs.elki.result.ResultHierarchy
add(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray: Append a value.
add(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.IntegerArray: Append a value.
add(K) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap
add(K, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap
add(K) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap
add(K, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap
add(K) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
add(K, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap
add(K) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
add(K, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap
add(double) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleHeap: Add a key-value pair to the heap
add(double, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleHeap: Add a key-value pair to the heap, except if the new element is larger than the top, and we are at design size (overflow)
add(double, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerHeap: Add a key-value pair to the heap
add(double, int, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerHeap: Add a key-value pair to the heap if it improves the top.
add(double, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap
add(double, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap
add(double, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap
add(double, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap
add(double, long) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongHeap: Add a key-value pair to the heap
add(double, long, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongHeap: Add a key-value pair to the heap if it improves the top.
add(double, long) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap
add(double, long, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap
add(double, long) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap
add(double, long, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap
add(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap
add(double, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap
add(double) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap
add(double, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap
add(double, V) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectHeap: Add a key-value pair to the heap
add(double, V, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectHeap: Add a key-value pair to the heap if it improves the top.
add(double, V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap
add(double, V, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap
add(double, V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap
add(double, V, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap
add(E) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap: Add an element to the heap.
add(int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerHeap: Add a key-value pair to the heap
add(int, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerHeap: Add a key-value pair to the heap, except if the new element is larger than the top, and we are at design size (overflow)
add(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMaxHeap
add(int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMaxHeap
add(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMinHeap
add(int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMinHeap
add(int, V) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectHeap: Add a key-value pair to the heap
add(int, V, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectHeap: Add a key-value pair to the heap if it improves the top.
add(int, V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap
add(int, V, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap
add(int, V) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap
add(int, V, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap
add(K) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ObjectHeap: Add a key-value pair to the heap
add(K, int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ObjectHeap: Add a key-value pair to the heap, except if the new element is larger than the top, and we are at design size (overflow)
add(E) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.TopBoundedHeap
add(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.UpdatableHeap
add(O, O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
add(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
add(O, O) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.ModifiableHierarchy: Add a parent-child relationship.
add(O) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.ModifiableHierarchy: Add an entry (initializes data structures).
add(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.PlotItem: Add a task to the item.
addActionListener(ActionListener) - Method in class de.lmu.ifi.dbs.elki.gui.util.TreePopup: Register an action listener.
addActionListener(ActionListener) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot: Adds an ActionListener to the plot.
addAlias(String, String) - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry: Register a class alias.
addAndSimplify(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geometry.XYCurve: Add a coordinate pair, performing curve simplification if possible.
addAxisReflection(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Add a reflection along the given axis.
addBackground(VisualizerContext) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView: Create a background node.
addBarChart(SVGPlot, Element, double, String, double, double, double, double, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization
addChangeListener(ChangeListener) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.AbstractParameterConfigurator
addChangeListener(ChangeListener) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
addChangeListener(ChangeListener) - Method in interface de.lmu.ifi.dbs.elki.gui.configurator.ParameterConfigurator: Add a change listener
addCheckBoxListener(ChangeListener) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGCheckbox: Register a listener for this checkbox.
addChild(Cluster<DendrogramModel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster: Add a child cluster.
addChild(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec: Add a child.
addChildCluster(Cluster<M>, Cluster<M>) - Method in class de.lmu.ifi.dbs.elki.data.Clustering: Add a cluster to the clustering.
addChildResult(Result) - Method in class de.lmu.ifi.dbs.elki.result.AbstractHierarchicalResult: Add a child result.
addChildResult(HierarchicalResult, Result) - Static method in class de.lmu.ifi.dbs.elki.result.ResultUtil: Add a child result.
addClass(CSSClass) - Method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClassManager: Add a single class to the map.
addCluster(GeneratorInterface) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorMain: Add a cluster to the cluster list.
addConstraint(ParameterConstraint<? super Integer>) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.ListEachConstraint: Add a constraint to this operator.
addConstraint(ParameterConstraint<? super T>) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter
addConstraint(ParameterConstraint<? super T>) - Method in interface de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.Parameter: Add an additional constraint.
AddCSSClass - Class in de.lmu.ifi.dbs.elki.visualization.batikutil: Add a CSS class to the event target.
AddCSSClass(String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.AddCSSClass: Constructor
addCSSClass(Element, String) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil: Add a CSS class to an Element.
addCSSClasses() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization.Instance: Adds the required CSS-Classes
addCSSClasses() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance: Adds the required CSS-Classes
addCSSClasses() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance: Adds the required CSS-Classes
addCSSClasses() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(int) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance: Define and add required CSS classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisReorderVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.index.RTreeParallelVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.ParallelAxisVisualization.Instance: Add the main CSS classes.
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionAxisRangeVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionLineVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.VoronoiVisualization.Instance: Adds the required CSS-Classes.
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionConvexHullVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionCubeVisualization.Instance: Adds the required CSS-Classes
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance: Adds the required CSS-Classes.
addCSSClasses(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance: Adds the required CSS-Classes
addCSSClassOrLogError(CSSClass) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Convenience method to add a CSS class or log an error.
addDataStoreListener(DataStoreListener) - Method in class de.lmu.ifi.dbs.elki.database.AbstractDatabase
addDataStoreListener(DataStoreListener) - Method in interface de.lmu.ifi.dbs.elki.database.Database: Adds a listener for the DataStoreEvent posted after the content of the database changes.
addDataStoreListener(DataStoreListener) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext: Adds a listener for the DataStoreEvent posted after the content changes.
addDBIDs(DBIDs) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster: Add new objects to the cluster.
addDBIDs(DBIDs) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
addDBIDs(DBIDs) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TroveHashSetModifiableDBIDs
addDBIDs(DBIDs) - Method in interface de.lmu.ifi.dbs.elki.database.ids.ModifiableDBIDs: Add DBIDs to collection.
addDenseUnit(CLIQUEUnit<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace: Adds the specified dense unit to this subspace.
addDirectoryEntry(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Adds a new directory entry to this node's children and returns the index of the entry in this node's children array.
addDirectoryEntry(E) - Method in interface de.lmu.ifi.dbs.elki.index.tree.Node: Adds a new directory entry to this node's children and returns the index of the entry in this node's children array.
addEdge(double, int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HeapMSTCollector
addEdge(double, int, int) - Method in interface de.lmu.ifi.dbs.elki.math.geometry.PrimsMinimumSpanningTree.Collector: Add a new edge to the output.
addend - Static variable in class de.lmu.ifi.dbs.elki.math.random.FastNonThreadsafeRandom
addEntry(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Adds the specified entry to the entries array and increases the numEntries counter.
addEventListener(Element, int, SVGArrow.Direction) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisReorderVisualization.Instance: Add an event listener to the Element
addEventListener(Element, int) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance: Add an event listener to the Element
addEventListener(Element, int) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.ParallelAxisVisualization.Instance: Add an event listener to the Element.
addFeatureVector(DBIDRef, V) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit: Adds the id of the specified feature vector to this unit, if this unit contains the feature vector.
addFlag(OptionID) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization: Add a flag to the parameter list
addFlags(int) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask: Set a task flag.
addGenerator(Distribution) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: Add a new generator to the cluster.
addHandler(Handler) - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingConfiguration: Add a handler to the root logger.
addHeader(String) - Method in class de.lmu.ifi.dbs.elki.result.CollectionResult: Add header information
addHeader(String) - Method in class de.lmu.ifi.dbs.elki.result.EvaluationResult: Add a header line to this result.
addHeader(SVGPlot, Element, double, String) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization
addHit(String, Class<?>) - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry: If a name has been resolved, add it.
addInternal(double, int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList: Add an entry, consisting of distance and internal index.
addInternal(double, int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDListKNNHeap: Add a new element to the heap/list.
addInternal(DoubleIntegerDBIDPair) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList: Add an entry, consisting of distance and internal index.
ADDITIONAL_REFERENCE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AGNES: Additional historical reference for single-linkage.
ADDITIONAL_REFERENCE_1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.tests.StandardizedTwoSampleAndersonDarlingTest: Additional reference -- Darling's note on this equation
ADDITIONAL_REFERENCE_2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.tests.StandardizedTwoSampleAndersonDarlingTest: More detailed discussion by Pettitt
addKNNListener(KNNListener) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor: Adds a KNNListener which will be invoked when the kNNs of objects are changing.
addLabel(String) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGScoreBar: Set label (right of the bar)
addLeafEntry(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Adds a new leaf entry to this node's children and returns the index of the entry in this node's children array.
addLeafEntry(E) - Method in interface de.lmu.ifi.dbs.elki.index.tree.Node: Adds a new leaf entry to this node's children and returns the index of the entry in this node's children array.
addLightGradient(SVGPlot) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGEffects: Static method to prepare a SVG document for light gradient effects.
addListener(DataStoreListener) - Method in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: Adds a DataStoreListener for a DataStoreEvent posted after the content of the database changes.
addListener(ResultListener) - Method in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: Adds a ResultListener to be notified on new results.
addListeners() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisualization: Add the listeners according to the mask.
addMarker() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance: Add marker for the selected IDs to mtag
addMarkerRect(double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance: Create a rectangle as marker (Marker higher than plot!)
addMatrix(Matrix) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Add a matrix operation to the matrix.
addMeasure(String, double, double, double, boolean) - Method in class de.lmu.ifi.dbs.elki.result.EvaluationResult.MeasurementGroup: Add a single measurement.
addMeasure(String, double, double, double, double, boolean) - Method in class de.lmu.ifi.dbs.elki.result.EvaluationResult.MeasurementGroup: Add a single measurement.
addName(String) - Method in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry: Add a candidate.
addNewRelation(SimpleTypeInformation<?>) - Method in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: Add a new representation for the given meta.
addNotify() - Method in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.DispatchingPanel
addOrGet(E) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hash.Unique: Inserts a value into the set, unless it is already present.
addPanelListener(ParameterTabPanel) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel
addPanels(JTabbedPane) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.MultiStepGUI
addParameter(Object, Parameter<?>, TrackParameters) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.AbstractParameterConfigurator
addParameter(Object, Parameter<?>, TrackParameters) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassListParameterConfigurator
addParameter(Object, Parameter<?>, TrackParameters) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassParameterConfigurator
addParameter(Object, Parameter<?>, TrackParameters) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel: Add parameter to this panel.
addParameter(Object, Parameter<?>, TrackParameters) - Method in interface de.lmu.ifi.dbs.elki.gui.configurator.ParameterConfigurator: Add a parameter to the panel.
addParameter(Parameter<?>, String, int, int) - Method in class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters: Add a single parameter to the list
addParameter(OptionID, Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization: Add a parameter to the parameter list
addParent(O) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec: Add a parent.
addProgress(Progress) - Method in class de.lmu.ifi.dbs.elki.logging.progress.ProgressTracker: Add a new Progress to the tracker.
addProgressBar(JProgressBar) - Method in class de.lmu.ifi.dbs.elki.gui.util.LogPanel: Add a new progress bar.
addQuotedString(Object) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Add a string in quotes.
addRecursively(ArrayList<Vector>, Hierarchy<Cluster<Model>>, Cluster<Model>) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization.Instance: Recursively add a cluster and its children.
addReference(Object, Reference, List<Pair<Reference, TreeSet<Object>>>, Map<Reference, TreeSet<Object>>) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
addRelation(Relation<?>) - Method in class de.lmu.ifi.dbs.elki.database.ProxyDatabase: Add a new representation.
addResultListener(ResultListener) - Method in class de.lmu.ifi.dbs.elki.result.ResultHierarchy: Register a result listener.
addResultListener(ResultListener) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext: Register a result listener.
addRotation(int, int, double) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: Apply a rotation to the generator
addRotation(int, int, double) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Convenience function to apply a rotation in 2 dimensions.
addScaling(double) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Simple linear (symmetric) scaling.
addSeparator() - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Add a separator
addShadowFilter(SVGPlot) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGEffects: Static method to prepare a SVG document for drop shadow effects.
AddSingleScale - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
AddSingleScale(double[]) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.AddSingleScale: Constructor.
AddSingleScale.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Parameterization class.
AddSingleScale.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.AddSingleScale.Parameterizer
addSingleton(SimplifiedHierarchyExtraction.TempCluster, DBIDRef, double, boolean) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction: Add a singleton object, as point or cluster.
addToFirst(E, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.Assignments: Add an entry to the first set.
addToplevelCluster(Cluster<M>) - Method in class de.lmu.ifi.dbs.elki.data.Clustering: Add a cluster to the clustering.
addToSecond(E, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.Assignments: Add an entry to the second set.
addToTies(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNHeap: Ensure the ties array has capacity for at least one more element.
addTranslation(Vector) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: Add a translation to the generator
addTranslation(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Add a translation operation to the matrix
addTranslation(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Add a translation operation to the matrix
addUpdateFlags(int) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask: Set (OR) the update flags.
addUpdateRunner(UpdateRunner) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.JSVGUpdateSynchronizer
addUpdateRunner(UpdateRunner) - Method in interface de.lmu.ifi.dbs.elki.visualization.svg.UpdateSynchronizer: Set an update runner to use.
addVis(Object, VisualizationItem) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext: Add (register) a visualization.
addVisualizationListener(VisualizationListener) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizationTree: Add a listener.
addVisualizationListener(VisualizationListener) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizerContext: Add a listener.
adjust - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Apply adjustment heuristic for interval choosing.
adjust - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH.Parameterizer: Apply adjustment heuristic for interval choosing.
adjust(Matrix, Matrix, Vector, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO: Inserts the specified vector into the given orthonormal matrix v at column corrDim.
ADJUST_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH.Parameterizer: Flag to indicate that an adjustment of the applied heuristic for choosing an interval is performed after an interval is selected.
adjustApproximatedKNNDistances(MkAppEntry, Map<DBID, KNNList>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree: Adjusts the knn distance in the subtree of the specified root entry.
adjustApproximatedKNNDistances(MkCoPEntry, Map<DBID, KNNList>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree: Adjusts the knn distance in the subtree of the specified root entry.
adjustedEps(int) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.KernelDensityEstimator: Rescale the query radius based on the given dimensionality.
adjustedRandIndex() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.PairCounting: Computes the adjusted Rand index (ARI).
adjustEntry(E, DBID, double, AbstractMTree<O, N, E, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode: Adjusts the parameters of the entry representing this node (e.g. after insertion of new objects).
adjustEntry(MkAppEntry, DBID, double, AbstractMTree<O, MkAppTreeNode<O>, MkAppEntry, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTreeNode: Adjusts the parameters of the entry representing this node.
adjustEntry(MkCoPEntry, DBID, double, AbstractMTree<O, MkCoPTreeNode<O>, MkCoPEntry, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTreeNode
adjustEntry(MkMaxEntry, DBID, double, AbstractMTree<O, MkMaxTreeNode<O>, MkMaxEntry, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeNode: Calls the super method and adjust additionally the k-nearest neighbor distance of this node as the maximum of the k-nearest neighbor distances of all its entries.
adjustEntry(MkTabEntry, DBID, double, AbstractMTree<O, MkTabTreeNode<O>, MkTabEntry, ?>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTreeNode
adjustEntry(E) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode: Adjusts the parameters of the entry representing this node.
adjustEntry(DeLiCluEntry) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluNode
adjustEntry(RdKNNEntry) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNNode
adjustEntryIncremental(E, SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTreeNode: Adjusts the parameters of the entry representing this node.
adjustKNNDistance(RdKNNEntry, ArrayDBIDs, List<? extends KNNList>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree: Adjusts the knn distance in the subtree of the specified root entry.
adjustTree(IndexTreePath<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree: Adjusts the tree after insertion of some nodes.
adjustTree(IndexTreePath<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree: Adjusts the tree after insertion of some nodes.
advance() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDArrayIter
advance(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDArrayIter
advance() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDIter
advance() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDListIter
advance(int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDListIter
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.KNNSubList.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.KNNSubList.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.MaskedDBIDs.DBIDItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.MaskedDBIDs.InvDBIDItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableArrayDBIDs.UnmodifiableDBIDArrayIter
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableArrayDBIDs.UnmodifiableDBIDArrayIter
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableDBIDs.UnmodifiableDBIDIter
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice.SliceItr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice.SliceItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice.SliceItr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice.SliceItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDKNNSubList.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDKNNSubList.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice.SliceItr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice.SliceItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar.Itr
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TroveHashSetModifiableDBIDs.Itr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TroveHashSetModifiableDBIDs.Itr.TIntHashItr
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerArrayDBIDs.UnmodifiableDBIDIter
advance(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerArrayDBIDs.UnmodifiableDBIDIter
advance() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerDBIDs.UnmodifiableDBIDIter
advance() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.AbstractVectorIter
advance(int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.AbstractVectorIter
advance(int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DecreasingVectorIter
advance() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DistanceResultAdapter
advance() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.FilteredDistanceResultAdapter
advance(int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.IncreasingVectorIter
advance() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.OutlierScoreAdapter
advance() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.SimpleAdapter
advance() - Method in class de.lmu.ifi.dbs.elki.math.geometry.XYCurve.Itr: Advance the iterator to the next position.
advance() - Method in class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve.Itr: Advance the iterator to the next position.
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparableMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.ComparatorMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap.UnorderedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMaxHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerObjectMinHeap.UnsortedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.FilteredIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrAll
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrAnc
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrDesc
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec.ItrChildren
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec.ItrChildrenReverse
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec.ItrParents
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec.ItrParentsReverse
advance() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.Hierarchy.Iter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.StackedIter
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractStaticHistogram.Iter
advance(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractStaticHistogram.Iter
advance() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayIter
advance(int) - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayIter: Moves the iterator forward or backward by the given offset.
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayListIter
advance(int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayListIter
advance() - Method in interface de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.Iter: Moves the iterator forward to the next entry.
advance() - Method in class de.lmu.ifi.dbs.elki.utilities.io.Tokenizer
affectedkNN(List<? extends KNNList>, DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor: Extracts and removes the DBIDs in the given collections.
affectedRkNN(List<? extends Collection<DoubleDBIDPair>>, DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor: Extracts and removes the DBIDs in the given collections.
AffineProjection - Class in de.lmu.ifi.dbs.elki.visualization.projections: Affine projections are the most general class.
AffineProjection(Projector, LinearScale[], AffineTransformation) - Constructor for class de.lmu.ifi.dbs.elki.visualization.projections.AffineProjection: Constructor with a given database and axes.
AffineTransformation - Class in de.lmu.ifi.dbs.elki.math.linearalgebra: Affine transformations implemented using homogeneous coordinates.
AffineTransformation(int) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Constructor for an identity transformation.
AffineTransformation(int, Matrix, Matrix) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Trivial constructor with all fields, mostly for cloning
AffinityPropagationClusteringAlgorithm<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Cluster analysis by affinity propagation.
AffinityPropagationClusteringAlgorithm(AffinityPropagationInitialization<O>, double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.AffinityPropagationClusteringAlgorithm: Constructor.
AffinityPropagationClusteringAlgorithm.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Parameterization class.
AffinityPropagationClusteringAlgorithm.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.AffinityPropagationClusteringAlgorithm.Parameterizer
AffinityPropagationInitialization<O> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Initialization methods for affinity propagation.
Afinal - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.SigmoidOutlierScalingFunction: Sigmoid parameter
agg - Variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators: Aggregation method.
agg - Variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer: Aggregation method.
AggarwalYuEvolutionary<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Evolutionary variant (EAFOD) of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
AggarwalYuEvolutionary(int, int, int, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary: Constructor.
AggarwalYuEvolutionary.EvolutionarySearch - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: The inner class to handle the actual evolutionary computation.
AggarwalYuEvolutionary.EvolutionarySearch(Relation<V>, ArrayList<ArrayList<DBIDs>>, int, Random) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch: Constructor.
AggarwalYuEvolutionary.Individuum - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Individuum for the evolutionary search.
AggarwalYuEvolutionary.Individuum(double, short[]) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum: Constructor
AggarwalYuEvolutionary.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Parameterization class.
AggarwalYuEvolutionary.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Parameterizer
AggarwalYuNaive<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: BruteForce variant of the high-dimensional outlier detection algorithm by Aggarwal and Yu.
AggarwalYuNaive(int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuNaive: Constructor.
AggarwalYuNaive.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Parameterization class.
AggarwalYuNaive.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuNaive.Parameterizer
aggregate - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster: Mass aggregate.
aggregate(double[]) - Method in enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Aggregate values.
aggregate(T, T) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Rule to combine two bins or entries into one.
AGGREGATE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer: Aggregation method.
AggregatedHillEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality: Estimator using the weighted average of multiple hill estimators.
AggregatedHillEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AggregatedHillEstimator
AggregatedHillEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality: Parameterization class.
AggregatedHillEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AggregatedHillEstimator.Parameterizer
aggregateSpecial(T, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Aggregate for a special value.
AGNES<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Hierarchical Agglomerative Clustering (HAC) or Agglomerative Nesting (AGNES) is a classic hierarchical clustering algorithm.
AGNES(DistanceFunction<? super O>, LinkageMethod) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AGNES: Constructor.
AGNES.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Parameterization class
AGNES.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AGNES.Parameterizer
AkaikeInformationCriterion - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality: Akaike Information Criterion (AIC).
AkaikeInformationCriterion() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.AkaikeInformationCriterion
ALGO_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.Parameterizer: Parameter that specifies which outlier detection algorithm to use on the resulting set of high contrast subspaces.
Algorithm - Interface in de.lmu.ifi.dbs.elki.algorithm: Specifies the requirements for any algorithm that is to be executable by the main class.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy: Clustering algorithm to run to obtain the hierarchy.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy.Parameterizer: The hierarchical clustering algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction: Clustering algorithm to run to obtain the hierarchy.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.Parameterizer: The hierarchical clustering algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction: Clustering algorithm to run to obtain the hierarchy.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.Parameterizer: The hierarchical clustering algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.RescaleMetaOutlierAlgorithm: Holds the algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.RescaleMetaOutlierAlgorithm.Parameterizer: Holds the algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1.Parameterizer: Clustering algorithm to run.
algorithm - Variable in class de.lmu.ifi.dbs.elki.application.ClassifierHoldoutEvaluationTask: Classifier to evaluate.
algorithm - Variable in class de.lmu.ifi.dbs.elki.application.ClassifierHoldoutEvaluationTask.Parameterizer: Classifier to evaluate.
ALGORITHM_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer: Parameter to hand an algorithm to be wrapped and run to our instance of RepresentativeUncertainClustering.
ALGORITHM_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1.Parameterizer: Clustering algorithm to use.
ALGORITHM_ID - Static variable in class de.lmu.ifi.dbs.elki.workflow.AlgorithmStep.Parameterizer: Parameter to specify the algorithm to run.
algorithms - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.SimpleOutlierEnsemble: The algorithms to run.
algorithms - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.SimpleOutlierEnsemble.Parameterizer: The algorithms to run.
algorithms - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel: The data input configured
algorithms - Variable in class de.lmu.ifi.dbs.elki.workflow.AlgorithmStep: Holds the algorithm to run.
algorithms - Variable in class de.lmu.ifi.dbs.elki.workflow.AlgorithmStep.Parameterizer: Holds the algorithm to run.
algorithmStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask: The algorithm (data mining) step.
algorithmStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask.Parameterizer
AlgorithmStep - Class in de.lmu.ifi.dbs.elki.workflow: The "algorithms" step, where data is analyzed.
AlgorithmStep(List<Algorithm>) - Constructor for class de.lmu.ifi.dbs.elki.workflow.AlgorithmStep: Constructor.
AlgorithmStep.Parameterizer - Class in de.lmu.ifi.dbs.elki.workflow: Parameterization class.
AlgorithmStep.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.workflow.AlgorithmStep.Parameterizer
AlgorithmTabPanel - Class in de.lmu.ifi.dbs.elki.gui.multistep.panels: Panel to handle data processing
AlgorithmTabPanel(InputTabPanel) - Constructor for class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel: Constructor.
algs - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel: Algorithm step to run on.
algTab - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.MultiStepGUI: Algorithm panel.
Alias - Annotation Type in de.lmu.ifi.dbs.elki.utilities: This interface defines alias names for classes.
aliases - Variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry: Aliases hash map.
aliaslen - Variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry: Occupied entries in aliases.
alignColumns(ObjectBundle) - Method in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: Find a mapping from package columns to database columns, eventually adding new database columns when needed.
alignLabels(List<ClassLabel>, double[], Collection<ClassLabel>) - Method in class de.lmu.ifi.dbs.elki.algorithm.classification.AbstractClassifier: Align the labels for a label query.
ALL - Static variable in interface de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.CellVisitor: Different modes of operation.
ALL_PROCESSORS - Static variable in class de.lmu.ifi.dbs.elki.parallel.ParallelCore: The number of CPUs to use.
allClassLabels(MultipleObjectsBundle) - Static method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.AbstractHoldout: Get an array of all class labels in a given data set.
allClassLabels(MultipleObjectsBundle, int) - Static method in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.AbstractHoldout: Get an array of all class labels in a given data set.
allM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.BiclusterCandidate: Mean of the current bicluster.
AllOrNoneMustBeSetGlobalConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints: Global parameter constraint specifying that either all elements of a list of parameters (Parameter) must be set, or none of them.
AllOrNoneMustBeSetGlobalConstraint(Parameter<?>...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.AllOrNoneMustBeSetGlobalConstraint: Constructs a global parameter constraint for testing if either all elements of a list of parameters are set or none of them.
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisFactory: Test whether to do a thumbnail or a full rendering.
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.ColoredHistogramVisualizer
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotVisualizer
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterParallelMeanVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.ParallelAxisVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AxisVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.HistogramVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.KeyVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.LabelVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.PixmapVisualizer
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.SettingsVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.SimilarityMatrixVisualizer
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYCurveVisualization
allowThumbnails(VisualizationTask) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.XYPlotVisualization
ALMOST_ONE - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.HaltonUniformDistribution: Threshold
almostEquals(Object, double) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Compare two matrices with a delta parameter to take numerical errors into account.
almostEquals(Object) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Compare two matrices with a delta parameter to take numerical errors into account.
almostEquals(double[][], double[][], double) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: Compare two matrices with a delta parameter to take numerical errors into account.
almostEquals(double[][], double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: Compare two matrices with a delta parameter to take numerical errors into account.
ALOCI<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof: Fast Outlier Detection Using the "approximate Local Correlation Integral".
ALOCI(NumberVectorDistanceFunction<?>, int, int, int, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI: Constructor.
ALOCI.ALOCIQuadTree - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof: Simple quadtree for ALOCI.
ALOCI.ALOCIQuadTree(double[], double[], double[], int, Relation<? extends NumberVector>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.ALOCIQuadTree: Constructor.
ALOCI.Node - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof: Node of the ALOCI Quadtree
ALOCI.Node(int, Vector, int, int, List<ALOCI.Node>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Node: Constructor.
ALOCI.Parameterizer<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.lof: Parameterization class.
ALOCI.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer
alongTrackDistanceDeg(double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil: The along track distance, is the distance from S to Q along the track S to E.
alongTrackDistanceDeg(double, double, double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil: The along track distance, is the distance from S to Q along the track S to E.
alongTrackDistanceRad(double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil: The along track distance, is the distance from S to Q along the track S to E.
alongTrackDistanceRad(double, double, double, double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil: The along track distance, is the distance from S to Q along the track S to E.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch: The parameter for multiple node deletion.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: The parameter for multiple node deletion.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS: Holds the value of ORCLUS.Parameterizer.ALPHA_ID.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.Parameterizer
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC: Alpha parameter.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC.Parameterizer: Alpha parameter.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC: Relative density threshold parameter alpha.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC.Parameterizer: Relative density threshold parameter Alpha.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC: Holds the maximum diversion allowed.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Parameterizer: Alpha parameter.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C: Alpha threshold for testing.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer: Parameter for the chi squared test threshold.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering: Alpha parameter for confidence.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer: Alpha parameter for confidence.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI: Alpha (level difference of sampling and counting neighborhoods)
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer: Alpha: number of levels difference to use in comparison
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI: Scaling of averaging neighborhood.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.Parameterizer: Scaling of averaging neighborhood.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS: Alpha threshold.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.Parameterizer: Holds the value of HiCS.Parameterizer.ALPHA_ID.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm: Parameter Alpha - significance niveau
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm.Parameterizer: Parameter Alpha - significance niveau
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC: Parameter alpha: Attribute difference exponent.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer: Parameter alpha: scaling.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1: Weighting parameter of size vs. dimensionality score.
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1.Parameterizer: Alpha parameter to balance parameters
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.SOD: Alpha (discriminance value).
alpha - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.SOD.Parameterizer: Alpha (discriminance value).
alpha - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization: Expected outlier rate alpha.
alpha - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer: Expected outlier rate alpha.
alpha - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex: Holds the value of parameter alpha.
alpha - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory: Holds the value of parameter HiSCPreferenceVectorIndex.Factory.ALPHA_ID.
alpha - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory.Parameterizer: Holds the value of parameter HiSCPreferenceVectorIndex.Factory.ALPHA_ID.
alpha - Variable in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HiCSDimensionSimilarity: Alpha threshold
alpha - Variable in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HiCSDimensionSimilarity.Parameterizer: Holds the value of HiCS.Parameterizer.ALPHA_ID .
alpha - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod: Working space for alphas
alpha - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PercentageEigenPairFilter: The threshold for strong eigenvectors: the strong eigenvectors explain a portion of at least alpha of the total variance.
alpha - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PercentageEigenPairFilter.Parameterizer: The threshold for strong eigenvectors: the strong eigenvectors explain a portion of at least alpha of the total variance.
alpha - Variable in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HiCSDependenceMeasure.Parameterizer: Holds the value of HiCS.Parameterizer.ALPHA_ID .
alpha - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution: Shape parameter of beta distribution
alpha - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution.Parameterizer: Parameters.
alpha - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScalingFunction: Mixing parameter alpha
alpha - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster.ClusterOutlineVisualization.Parameterizer: Alpha value
alpha - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization.Parameterizer: Alpha value
alpha2 - Variable in class de.lmu.ifi.dbs.elki.math.geometry.AlphaShape: Alpha shape
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: Parameter for multiple node deletion to accelerate the algorithm.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Parameterizer: The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain a portion of at least alpha of the total variance.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS.Parameterizer: Parameter to specify the factor for reducing the number of current clusters in each iteration, must be an integer greater than 0 and less than 1.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC.Parameterizer: Parameter for the maximum density difference.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC.Parameterizer: Relative density threshold parameter Alpha.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer: Alpha parameter for confidence estimation.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer: Parameter to specify the averaging neighborhood scaling.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.Parameterizer: Parameter to specify the averaging neighborhood scaling.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.HiCS.Parameterizer: Parameter that determines the size of the test statistic during the Monte-Carlo iteration.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm.Parameterizer: Holds the alpha value - significance niveau
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC.Parameterizer: Parameter to specify alpha.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OutRankS1.Parameterizer: Alpha parameter for S1
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.SOD.Parameterizer: Parameter to indicate the multiplier for the discriminance value for discerning small from large variances.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer: Shape parameter.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory: The maximum absolute variance along a coordinate axis.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PercentageEigenPairFilter.Parameterizer: The threshold for 'strong' eigenvectors: the 'strong' eigenvectors explain a portion of at least alpha of the total variance.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.BetaDistribution.Parameterizer: Alpha parameter.
ALPHA_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.ClusterHullVisualization.Parameterizer: Alpha-Value for alpha-shapes Key: -hull.alpha
ALPHA_THRESHOLD_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer: Parameter for the chi squared test threshold.
alphaBetaPWM(A, NumberArrayAdapter<?, A>, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.ProbabilityWeightedMoments: Compute the alpha_r and beta_r factors in parallel using the method of probability-weighted moments.
alphaExtremum - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Holds the alpha values of the global extremum.
alphaPWM(A, NumberArrayAdapter<?, A>, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.ProbabilityWeightedMoments: Compute the alpha_r factors using the method of probability-weighted moments.
AlphaShape - Class in de.lmu.ifi.dbs.elki.math.geometry: Compute the alpha-Shape of a point set, using Delaunay triangulation.
AlphaShape(List<Vector>, double) - Constructor for class de.lmu.ifi.dbs.elki.math.geometry.AlphaShape
alphasqrt - Variable in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HiCSDependenceMeasure: Alpha threshold
AlternativeTypeInformation - Class in de.lmu.ifi.dbs.elki.data.type: Class that combines multiple type restrictions into one using the "or" operator.
AlternativeTypeInformation(TypeInformation...) - Constructor for class de.lmu.ifi.dbs.elki.data.type.AlternativeTypeInformation: Constructor.
andCMax(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: AND o onto v in a copy, i.e. v & o The resulting array will have the shorter length of the two.
andCMin(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: AND o onto v in a copy, i.e. v & o The resulting array will have the shorter length of the two.
AnderbergHierarchicalClustering<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: This is a modification of the classic AGNES algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
AnderbergHierarchicalClustering(DistanceFunction<? super O>, LinkageMethod) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AnderbergHierarchicalClustering: Constructor.
AnderbergHierarchicalClustering.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Parameterization class
AnderbergHierarchicalClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AnderbergHierarchicalClustering.Parameterizer
AndersonDarlingTest - Class in de.lmu.ifi.dbs.elki.math.statistics.tests: Perform Anderson-Darling test for a Gaussian distribution.
AndersonDarlingTest() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.tests.AndersonDarlingTest
andI(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: AND o onto v inplace, i.e. v &= o
andI(long[], long[], int) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil: AND o onto v inplace, i.e. v &= (o << off)
andOnto(long[]) - Method in class de.lmu.ifi.dbs.elki.data.BitVector: Combine onto v using the AND operation, i.e.
angle(NumberVector, NumberVector, Vector) - Static method in class de.lmu.ifi.dbs.elki.data.VectorUtil: Compute the angle between two vectors.
angle(NumberVector, NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.data.VectorUtil: Compute the angle between two vectors.
angle(Vector, Vector) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Compute the angle between two vectors.
angle(double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Compute the angle between two vectors.
angle(Vector, Vector, Vector) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Compute the angle between two vectors.
angle(double[], double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Compute the angle between two vectors.
angleSparse(SparseNumberVector, SparseNumberVector) - Static method in class de.lmu.ifi.dbs.elki.data.VectorUtil: Compute the angle for sparse vectors.
AngTanLinearSplit - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split: Line-time complexity split proposed by Ang and Tan.
AngTanLinearSplit() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.AngTanLinearSplit
AngTanLinearSplit.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split: Parameterization class.
AngTanLinearSplit.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.AngTanLinearSplit.Parameterizer
ANY - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Input type for algorithms that accept anything.
APIViolationException - Exception in de.lmu.ifi.dbs.elki.utilities.exceptions: This class indicates an exception likely caused by an API not implemented correctly.
APIViolationException(String) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.APIViolationException: Constructor.
APIViolationException(String, Throwable) - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.APIViolationException: Constructor.
APP_PREFIX - Variable in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI: Prefix for application package.
appCombo - Variable in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI: Combo box for choosing the application to run.
append(double, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.DoubleIntArrayList: Append a key-value pair.
append(double) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append double
append(int) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append integer
append(double[]) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append double array
append(int[]) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append integer array
append(SimpleTypeInformation<?>, Object) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle: Append a single representation to the object.
append - Variable in class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper: Always append to the output file.
append - Variable in class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper.Parameterizer: Always append to the output file.
append(String, double...) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath: Append an action to the current path.
APPEND_ID - Static variable in class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper.Parameterizer: Append flag.
appendCauses(StringBuilder, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.ErrorFormatter: Append (pruned) stack traces for associated exceptions.
appendClassRestriction(Document, Class<?>, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendClassRestrictionWiki(DocumentParameters.WikiStream, Class<?>) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendColumn(SimpleTypeInformation<?>, List<?>) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle: Helper to add a single column to the bundle.
appendColumns(Matrix) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Returns a matrix which consists of this matrix and the specified columns.
appendColumns(double[][], double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: Returns a matrix which consists of this matrix and the specified columns.
appendCSSDefinition(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.visualization.css.CSSClass: Append CSS definition to a stream
appendDefaultClassLink(Document, Parameter<?>, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendDefaultValueIfSet(Document, Parameter<?>, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters: Append string containing the default value.
appendDefaultValueWiki(DocumentParameters.WikiStream, Parameter<?>) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendKeyArray(Object) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append a key an start a new array
appendKeyHash(Object) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append a key an start a new hash
appendKeyValue(Object, Object) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append a key-value pair as string.
appendKnownImplementationsIfNonempty(Document, Class<?>, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendKnownImplementationsWiki(DocumentParameters.WikiStream, Class<?>) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendMultilineText(Document, Element, String) - Static method in class de.lmu.ifi.dbs.elki.utilities.xml.HTMLUtil: Append a multiline text to a node, transforming linewraps into BR tags.
appendMultilineTextWiki(DocumentParameters.WikiStream, String) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendNewline() - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append a newline, for human readability
appendNoClassRestriction(Document, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendNoClassRestrictionWiki(DocumentParameters.WikiStream) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendNoDefaultValue(Document, Element) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters: Append string that there is not default value.
appendNoDefaultValueWiki(DocumentParameters.WikiStream) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
appendParameterization(Parameterization) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization: Append a new Parameterization to the chain.
appendParameters(ListParameterization) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.AbstractParameterConfigurator
appendParameters(ListParameterization) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassListParameterConfigurator
appendParameters(ListParameterization) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ClassParameterConfigurator
appendParameters(ListParameterization) - Method in class de.lmu.ifi.dbs.elki.gui.configurator.ConfiguratorPanel
appendParameters(ListParameterization) - Method in interface de.lmu.ifi.dbs.elki.gui.configurator.ParameterConfigurator: Append the parameters to a list.
appendParameters(ListParameterization) - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel: Collect parameters
appendSimple(Object...) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle: Append a new record to the data set.
appendSpace(StringBuilder, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Append whitespace to a buffer.
appendString(Object) - Method in class de.lmu.ifi.dbs.elki.application.jsmap.JSONBuffer: Append a string in quotes
appendTo(StringBuilder, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset
appendTo(StringBuilder, FPGrowth.FPNode.Translator) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode: Debugging function: build a text representation of the tree.
appendTo(StringBuilder, FPGrowth.FPNode.Translator, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode: Debugging function: build a text representation of the tree.
appendTo(StringBuilder, int) - Method in interface de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode.Translator: Append a single item to a buffer.
appendTo(StringBuilder, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Itemset: Append to a string buffer.
appendTo(StringBuilder, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset
appendTo(StringBuilder, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset
appendTo(StringBuilder, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SparseItemset
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.data.spatial.Polygon: Append the polygon to the buffer.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.data.spatial.PolygonsObject: Append polygons to the buffer.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.logging.progress.AbstractProgress: Serialize a description into a String buffer.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress: Append a string representation of the progress to the given string buffer.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.logging.progress.IndefiniteProgress: Serialize 'indefinite' progress.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.logging.progress.MutableProgress: Serialize 'indefinite' progress.
appendToBuffer(StringBuilder) - Method in interface de.lmu.ifi.dbs.elki.logging.progress.Progress: Serialize a description into a String buffer.
appendToBuffer(StringBuilder) - Method in class de.lmu.ifi.dbs.elki.logging.progress.StepProgress
appendZeros(StringBuilder, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.FormatUtil: Append zeros to a buffer.
apply(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the transformation onto a vector
apply(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the transformation onto a vector
applyInverse(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the inverse transformation onto a vector
applyInverse(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the inverse transformation onto a vector
applyPrescaling(ScalingFunction, Relation<NumberVector>, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment: Prescale each vector (except when in skip) with the given scaling function.
applyRelative(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the transformation onto a vector
applyRelative(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the transformation onto a vector
applyRelativeInverse(Vector) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the inverse transformation onto a vector
applyRelativeInverse(double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: Apply the inverse transformation onto a vector
applyScaling(double[], ScalingFunction) - Static method in class de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment
applySqrt(KNNList) - Static method in class de.lmu.ifi.dbs.elki.database.QueryUtil: Apply the square root function to each value in the list.
approx - Variable in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.PartialVACandidate: The actual approximation.
approximateBinomialCoefficient(int, int) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Binomial coefficent, also known as "n choose k").
approximateConservativeKnnDistance(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry: Returns the conservative approximated knn distance of the entry.
approximateConservativeKnnDistance(int) - Method in interface de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPEntry: Returns the conservative approximated knn distance of the entry.
approximateConservativeKnnDistance(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry: Returns the conservative approximated knn distance of the entry.
approximatedValueAt(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppDirectoryEntry: Returns the approximated value at the specified k.
approximatedValueAt(int) - Method in interface de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppEntry: Returns the approximated value at the specified k.
approximatedValueAt(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppLeafEntry: Returns the approximated value at the specified k.
approximateFactorial(int) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Compute the Factorial of n, often written as c!
approximateKnnDistances(double[]) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppTree: Computes the polynomial approximation of the specified knn-distances.
approximateKnnDistances(MkCoPLeafEntry, KNNList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree: Computes logarithmic skew (fractal dimension ie. m) and in kappx[0] and kappx[1] the non-logarithmic values of the approximated first and last nearest neighbor distances
approximateLowerHull(ConvexHull, double[], double, double, double[], double, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree: Approximates the lower hull.
approximatelyLinearDependent(PCAFilteredResult, PCAFilteredResult) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Instance: Returns true, if the strong eigenvectors of the two specified PCAs span up the same space.
approximateProgressiveKnnDistance(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry: Returns the progressive approximated knn distance of the entry.
approximateUpperHull(ConvexHull, double[], double[]) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
approximateUpperHull_OLD(ConvexHull, double[], double, double, double[], double, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
approximateUpperHull_PAPER(ConvexHull, double[], double, double, double[], double, double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree
approximation - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppDirectoryEntry: The polynomial approximation.
approximation - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp.MkAppLeafEntry: The polynomial approximation.
approximation - Variable in class de.lmu.ifi.dbs.elki.index.vafile.VectorApproximation: approximation (va cell ids)
ApproximationLine - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop: Provides an approximation for knn-distances line consisting of incline m, axes intercept t and a start value for k.
ApproximationLine() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine: Empty constructor for serialization purposes.
ApproximationLine(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine: Provides an approximation for knn-distances line consisting of incline m, axes intercept t and a start value for k.
ApproximativeLeastOverlapInsertionStrategy - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert: The choose subtree method proposed by the R*-Tree with slightly better performance for large leaf sizes (linear approximation).
ApproximativeLeastOverlapInsertionStrategy(int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy: Constructor.
ApproximativeLeastOverlapInsertionStrategy.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert: Parameterization class.
ApproximativeLeastOverlapInsertionStrategy.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.ApproximativeLeastOverlapInsertionStrategy.Parameterizer
APRIORI - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining: The APRIORI algorithm for Mining Association Rules.
APRIORI(double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI: Constructor with minimum frequency.
APRIORI(double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI: Constructor with minimum frequency.
APRIORI.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining: Parameterization class.
APRIORI.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI.Parameterizer
aprioriGenerate(List<? extends Itemset>, int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI: Prunes a given set of candidates to keep only those BitSets where all subsets of bits flipping one bit are frequent already.
ARBITRARY_SIMILARITY - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter.Parameterizer: Arbitrary Similarity functions
ArcCosineDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Cosine distance function for feature vectors.
ArcCosineDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.ArcCosineDistanceFunction: Deprecated.
Use static instance!
ArcCosineDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction: Parameterization class.
ArcCosineDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.ArcCosineDistanceFunction.Parameterizer
ArccosSimilarityAdapter<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Adapter from a normalized similarity function to a distance function using arccos(sim).
ArccosSimilarityAdapter(NormalizedSimilarityFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.ArccosSimilarityAdapter: Constructor.
ArccosSimilarityAdapter.Instance<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Distance function instance
ArccosSimilarityAdapter.Instance(Relation<O>, DistanceFunction<? super O>, SimilarityQuery<O>) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.ArccosSimilarityAdapter.Instance: Constructor.
ArccosSimilarityAdapter.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Parameterization class.
ArccosSimilarityAdapter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.ArccosSimilarityAdapter.Parameterizer
areas - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepAreaResult: Storage
areas - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSSteepAreaVisualization.Instance: Our clustering
areaUnderCurve(XYCurve) - Static method in class de.lmu.ifi.dbs.elki.math.geometry.XYCurve: Compute the area under curve for a curve monotonously increasing in X.
ARFF_COMMENT - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Comment pattern.
ARFF_HEADER_ATTRIBUTE - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Arff attribute declaration marker.
ARFF_HEADER_DATA - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Arff data marker.
ARFF_HEADER_RELATION - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Arff file marker.
ARFF_NUMERIC - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Pattern for numeric columns.
ArffParser - Class in de.lmu.ifi.dbs.elki.datasource.parser: Parser to load WEKA .arff files into ELKI.
ArffParser(Pattern, Pattern) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Constructor.
ArffParser(String, String) - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Constructor.
ArffParser.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.parser: Parameterization class.
ArffParser.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser.Parameterizer
arrange(VisualizerContext) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.HistogramProjector
arrange(VisualizerContext) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.OPTICSProjector
arrange(VisualizerContext) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.ParallelPlotProjector
arrange(VisualizerContext) - Method in interface de.lmu.ifi.dbs.elki.visualization.projector.Projector: Produce an arrangement of projections.
arrange(VisualizerContext) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.ScatterPlotProjector
arrangeVisualizations(double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot: Recompute the layout of visualizations.
array(TypeInformation...) - Static method in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Make a type array easily.
array - Variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskUpperTriangleMatrix: Data storage
array - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray: The array
ARRAY2D_ADAPTER - Static variable in class de.lmu.ifi.dbs.elki.math.geometry.PrimsMinimumSpanningTree: Adapter class for double[][] matrixes.
ArrayAdapter<T,A> - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Adapter for array-like things.
ArrayAdapterDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource: Import an existing data matrix (double[rows][cols]) into an ELKI database.
ArrayAdapterDatabaseConnection(double[][]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ArrayAdapterDatabaseConnection: Constructor.
ArrayAdapterDatabaseConnection(double[][], String[]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ArrayAdapterDatabaseConnection: Constructor.
ArrayAdapterDatabaseConnection(double[][], String[], Integer) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ArrayAdapterDatabaseConnection: Constructor.
ARRAYDBIDADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil: Use ArrayDBIDs as array.
ArrayDBIDs - Interface in de.lmu.ifi.dbs.elki.database.ids: Interface for array based DBIDs.
ArrayDBIDsAdapter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Use a DBID array in a generic array-like context.
ArrayDBIDsAdapter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayDBIDsAdapter: Constructor.
ArrayDBIDStore - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: A class to answer representation queries using the stored Array.
ArrayDBIDStore(int, DataStoreIDMap) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore: Constructor.
ArrayDoubleStore - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: A class to answer representation queries using the stored Array.
ArrayDoubleStore(int, DataStoreIDMap) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore: Constructor.
ArrayDoubleStore(int, DataStoreIDMap, double) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore: Constructor.
ArrayIntegerStore - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: A class to answer representation queries using the stored Array.
ArrayIntegerStore(int, DataStoreIDMap) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore: Constructor.
ArrayIntegerStore(int, DataStoreIDMap, int) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore: Constructor.
ArrayIter - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.iterator: Array iterators can also go backwards and seek.
ArrayLikeUtil - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Utility class that allows plug-in use of various "array-like" types such as lists in APIs that can take any kind of array to safe the cost of reorganizing the objects into a real array.
ArrayLikeUtil() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil: Fake constructor.
ArrayListIter<O> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.iterator: ELKI style Iterator for array lists.
ArrayListIter(List<O>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayListIter: Constructor.
ArrayModifiableDBIDs - Interface in de.lmu.ifi.dbs.elki.database.ids: Array-oriented implementation of a modifiable DBID collection.
ArrayModifiableIntegerDBIDs - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Class using a primitive int[] array as storage.
ArrayModifiableIntegerDBIDs(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs: Constructor.
ArrayModifiableIntegerDBIDs() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs: Constructor.
ArrayModifiableIntegerDBIDs(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs: Constructor.
ArrayModifiableIntegerDBIDs.Itr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Iterator class.
ArrayModifiableIntegerDBIDs.Itr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Itr
ArrayModifiableIntegerDBIDs.Slice - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Slice of an array.
ArrayModifiableIntegerDBIDs.Slice(int, int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice: Constructor.
ArrayModifiableIntegerDBIDs.Slice.SliceItr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Iterator class.
ArrayModifiableIntegerDBIDs.Slice.SliceItr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice.SliceItr
ArrayRecordStore - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: A class to answer representation queries using the stored Array.
ArrayRecordStore(Object[][], DataStoreIDMap) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore: Constructor with existing data
ArrayRecordStore.StorageAccessor<T> - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: Access a single record in the given data.
ArrayRecordStore.StorageAccessor(int) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore.StorageAccessor: Constructor.
arraysize(int) - Static method in class de.lmu.ifi.dbs.elki.persistent.OnDiskUpperTriangleMatrix: Compute the size of the needed backing array from the matrix dimensions.
ArrayStaticDBIDs - Interface in de.lmu.ifi.dbs.elki.database.ids: Unmodifiable, indexed DBIDs.
ArrayStaticIntegerDBIDs - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Static (no modifications allowed) set of Database Object IDs.
ArrayStaticIntegerDBIDs(int...) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs: Constructor.
ArrayStaticIntegerDBIDs.Itr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: DBID iterator in ELKI/C style.
ArrayStaticIntegerDBIDs.Itr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Itr
ArrayStaticIntegerDBIDs.Slice - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Slice of an array.
ArrayStaticIntegerDBIDs.Slice(int, int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice: Constructor.
ArrayStaticIntegerDBIDs.Slice.SliceItr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Iterator class.
ArrayStaticIntegerDBIDs.Slice.SliceItr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice.SliceItr
ArrayStore<T> - Class in de.lmu.ifi.dbs.elki.database.datastore.memory: A class to answer representation queries using the stored Array.
ArrayStore(Object[], DataStoreIDMap) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayStore: Constructor.
asByteArray(NumberVector) - Method in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.ZCurveTransformer: Transform a single vector.
asByteArray() - Method in class de.lmu.ifi.dbs.elki.persistent.DefaultPageHeader
asByteArray() - Method in interface de.lmu.ifi.dbs.elki.persistent.PageHeader: Return the header as byte array
ascending() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.AkaikeInformationCriterion
ascending() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.BayesianInformationCriterion
ascending() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.BayesianInformationCriterionZhao
ascending() - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.KMeansQualityMeasure: Use ascending or descending ordering.
ascending() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.WithinClusterMeanDistanceQualityMeasure
ascending() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality.WithinClusterVarianceQualityMeasure
ascending - Variable in class de.lmu.ifi.dbs.elki.result.OrderingFromDataStore: Factor for ascending (+1) and descending (-1) ordering.
ascending - Variable in class de.lmu.ifi.dbs.elki.result.outlier.OrderingFromRelation: Factor for ascending (+1) and descending (-1) ordering.
AsciiDistanceParser - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Parser for parsing one distance value per line.
AsciiDistanceParser(CSVReaderFormat) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.AsciiDistanceParser: Constructor.
AsciiDistanceParser.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Parameterization class.
AsciiDistanceParser.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.AsciiDistanceParser.Parameterizer
asDoubleArray() - Method in class de.lmu.ifi.dbs.elki.math.DoubleMinMax: Return minimum and maximum as array.
asIntArray() - Method in class de.lmu.ifi.dbs.elki.math.IntegerMinMax: Return minimum and maximum as array.
asInteger(DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Export a DBID as int.
asMultipleObjectsBundle() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleReader
asMultipleObjectsBundle() - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.BundleStreamSource: Return (or collect) the stream as bundle.
asMultipleObjectsBundle() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.StreamFromBundle
asMultipleObjectsBundle() - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamFilter
asMultipleObjectsBundle() - Method in class de.lmu.ifi.dbs.elki.datasource.parser.AbstractStreamingParser
aspectRatioLock - Variable in class de.lmu.ifi.dbs.elki.visualization.savedialog.SaveOptionsPanel
assertConfigured() - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingConfiguration: Assert that logging was configured.
assertConsistent() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.RectangleArranger
assertRange(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Assert that the presented ids constitute a continuous DBIDRange.
assertSameDimensionality(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil: Check that two spatial objects have the same dimensionality.
assertSortedByDistance(DoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner: Ensure that the results are sorted by distance.
assign(Relation<V>, DistanceQuery<V>, List<ORCLUS<V>.ORCLUSCluster>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ORCLUS: Creates a partitioning of the database by assigning each object to its closest seed.
assign(HashMap<String, DBIDs>, String, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelClustering: Assigns the specified id to the labelMap according to its label
assign(HashMap<String, DBIDs>, String, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.trivial.ByLabelHierarchicalClustering: Assigns the specified id to the labelMap according to its label
assignBest(Assignments<E>, long[], N, double[], int[], int, boolean) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.MTreeSplit: Assigns the first object of the specified list to the first assignment that it is not yet assigned to the second assignment.
assignDBID(DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleReader
assignDBID(DBIDVar) - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.BundleStreamSource: Assign the current object ID to a DBIDVar.
assignDBID(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle
assignDBID(int, DBIDVar) - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.ObjectBundle: Assign the object DBID to a variable
assignDBID(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle
assignDBID(DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.StreamFromBundle
assignDBID(DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamFilter
assignDBID(DBIDVar) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.AbstractStreamingParser
assigned - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEUnit: Flag that indicates if this unit is already assigned to a cluster.
assignment - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor: Assignment storage.
assignment - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor.Instance: Cluster assignment storage.
assignment - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation: Partition assignment and size.
assignment - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.StratifiedCrossValidation: Partition assignment, sizes
Assignments<E extends MTreeEntry> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split: Encapsulates the attributes of an assignment during a split.
Assignments(DBID, DBID, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.Assignments: Constructor.
Assignments(int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.Assignments: Constructor.
assignPoints(ArrayDBIDs, long[][], Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS: Assigns the objects to the clusters.
assignProbabilitiesToInstances(Relation<? extends NumberVector>, List<? extends EMClusterModel<?>>, WritableDataStore<double[]>) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM: Assigns the current probability values to the instances in the database and compute the expectation value of the current mixture of distributions.
assignRemainingToNearestCluster(ArrayDBIDs, DBIDs, DBIDs, WritableIntegerDataStore, DistanceQuery<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.CLARA: Returns a list of clusters.
assignToNearestCluster(Relation<? extends V>, List<? extends NumberVector>, List<? extends ModifiableDBIDs>, WritableIntegerDataStore, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans: Returns a list of clusters.
assignToNearestCluster(Relation<V>, DBIDs, List<? extends NumberVector>, double[][], int[], List<? extends ModifiableDBIDs>, WritableIntegerDataStore, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansBatchedLloyd: Returns a list of clusters.
assignToNearestCluster(Relation<V>, List<Vector>, List<ModifiableDBIDs>, WritableIntegerDataStore, double[], double[][], LongStatistic) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansCompare: Reassign objects, but only if their bounds indicate it is necessary to do so.
assignToNearestCluster(Relation<V>, List<Vector>, List<Vector>, List<ModifiableDBIDs>, WritableIntegerDataStore, double[], double[][], WritableDoubleDataStore, WritableDataStore<double[]>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansElkan: Reassign objects, but only if their bounds indicate it is necessary to do so.
assignToNearestCluster(Relation<V>, List<Vector>, List<Vector>, List<ModifiableDBIDs>, WritableIntegerDataStore, double[], WritableDoubleDataStore, WritableDoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly: Reassign objects, but only if their bounds indicate it is necessary to do so.
assignToNearestCluster(Relation<V>, List<Vector>, List<ModifiableDBIDs>, WritableIntegerDataStore, double[], double[][], int[][], LongStatistic) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansSort: Reassign objects, but only if their bounds indicate it is necessary to do so.
assignToNearestCluster(ArrayDBIDs, Mean[], List<? extends ModifiableDBIDs>, DistanceQuery<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsEM: Returns a list of clusters.
assignToNearestCluster(ArrayDBIDs, DBIDs, WritableDoubleDataStore, WritableDoubleDataStore, WritableIntegerDataStore, DistanceQuery<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsPAM: Returns a list of clusters.
assignToNearestCluster(Relation<DiscreteUncertainObject>, List<Vector>, List<? extends ModifiableDBIDs>, WritableIntegerDataStore, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.UKMeans: Returns a list of clusters.
assignUnassigned(Relation<V>, WritableDataStore<double[]>, List<MultivariateGaussianModel>, ModifiableDBIDs) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C: Assign unassigned objects to best candidate based on shortest Mahalanobis distance.
assignVar(DBIDRef, DBIDVar) - Method in interface de.lmu.ifi.dbs.elki.database.datastore.DBIDDataStore: Retrieves an object from the storage.
assignVar(DBIDRef, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore
assignVar(DBIDRef, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDBIDStore
assignVar(int, DBIDVar) - Method in interface de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs: Assign a DBID variable the value of position index.
assignVar(DBIDVar, int) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory: Assign an integer value to a DBID variable.
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.UnmodifiableArrayDBIDs
assignVar(DBIDVar, int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar
assignVar(int, DBIDVar) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.UnmodifiableIntegerArrayDBIDs
asStream() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle: Process this bundle as stream.
assumeVectorField(Relation<V>) - Static method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil: Get the vector field type information from a relation.
atmean - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierGammaScaling: Score at the mean, for cut-off.
AtomicLongCounter - Class in de.lmu.ifi.dbs.elki.logging.statistics: Class to count events in a thread-safe counter.
AtomicLongCounter(String) - Constructor for class de.lmu.ifi.dbs.elki.logging.statistics.AtomicLongCounter: Constructor.
attachPlot(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.JSVGSynchronizedCanvas: Attach to a new plot, and display.
attachToRelation(Database, Relation<?>, TIntArrayList, ArrayList<String>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering: Build a clustering from the file result.
ATTR_ANGLE - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Rotation angle
ATTR_AXIS1 - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: First axis for rotation plane
ATTR_AXIS2 - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Second axis for rotation plane
ATTR_DENSITY - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Density correction factor
ATTR_K - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Gamma k
ATTR_MAX - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Maximum value
ATTR_MEAN - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Mean
ATTR_MIN - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Minimum value
ATTR_NAME - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Cluster nane
ATTR_SEED - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Random seed
ATTR_SIZE - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Cluster size
ATTR_STDDEV - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Standard deviation
ATTR_TEST - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Attribute to control model testing
ATTR_THETA - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Gamma theta
ATTR_VECTOR - Static variable in class de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection: Vector
attribute - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.AttributeModifier: The name of the attribute to be modified.
ATTRIBUTE_CONCATENATION - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat: A sign to separate attributes.
ATTRIBUTE_SEPARATOR - Static variable in class de.lmu.ifi.dbs.elki.data.AbstractNumberVector: The String to separate attribute values in a String that represents the values.
AttributeModifier - Class in de.lmu.ifi.dbs.elki.visualization.batikutil: Runnable wrapper for modifying XML-Attributes.
AttributeModifier(Element, String, String) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.AttributeModifier: Trivial constructor.
attributes - Variable in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser: Double array storing the numerical attributes during parsing.
AttributeWiseBetaNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Project the data using a Beta distribution.
AttributeWiseBetaNormalization(List<DistributionEstimator<?>>, double) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization: Constructor.
AttributeWiseBetaNormalization.Adapter - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Array adapter class for vectors.
AttributeWiseBetaNormalization.Adapter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Adapter
AttributeWiseBetaNormalization.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Parameterization class.
AttributeWiseBetaNormalization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer
AttributeWiseCDFNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Class to perform and undo a normalization on real vectors by estimating the distribution of values along each dimension independently, then rescaling objects to the cumulative density function (CDF) value at the original coordinate.
AttributeWiseCDFNormalization(List<DistributionEstimator<?>>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization: Constructor.
AttributeWiseCDFNormalization.Adapter - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Array adapter class for vectors.
AttributeWiseCDFNormalization.Adapter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Adapter
AttributeWiseCDFNormalization.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Parameterization class.
AttributeWiseCDFNormalization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Parameterizer
AttributeWiseErfNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Attribute-wise Normalization using the error function.
AttributeWiseErfNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseErfNormalization: Constructor.
AttributeWiseMADNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Median Absolute Deviation is used for scaling the data set as follows: First, the median, and median absolute deviation are computed in each axis.
AttributeWiseMADNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMADNormalization: Constructor.
AttributeWiseMeanNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Normalization designed for data with a meaningful zero: Each attribute is scaled to have the same mean (but 0 is not changed).
AttributeWiseMeanNormalization(double[]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization: Constructor.
AttributeWiseMeanNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMeanNormalization: Constructor.
AttributeWiseMinMaxNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
AttributeWiseMinMaxNormalization(double[], double[]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization: Constructor.
AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Parameterization class.
AttributeWiseMinMaxNormalization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization.Parameterizer
AttributeWiseVarianceNormalization<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.
AttributeWiseVarianceNormalization(double[], double[]) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization: Constructor.
AttributeWiseVarianceNormalization() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization: Constructor.
AttributeWiseVarianceNormalization.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Parameterization class.
AttributeWiseVarianceNormalization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseVarianceNormalization.Parameterizer
auc - Variable in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierPrecisionRecallCurve.PRCurve: Area under curve
auc - Variable in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierROCCurve.ROCResult: AUC value
autoEvaluateClusterings(ResultHierarchy, Result) - Method in class de.lmu.ifi.dbs.elki.evaluation.AutomaticEvaluation
autoEvaluateOutliers(ResultHierarchy, Result) - Method in class de.lmu.ifi.dbs.elki.evaluation.AutomaticEvaluation
AUTOMAGIC_FORMAT - Static variable in class de.lmu.ifi.dbs.elki.visualization.savedialog.SVGSaveDialog: Automagic file format
AutomaticEvaluation - Class in de.lmu.ifi.dbs.elki.evaluation: Evaluator that tries to auto-run a number of evaluation methods.
AutomaticEvaluation() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.AutomaticEvaluation
AutomaticEvaluation.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation: Parameterization class
AutomaticEvaluation.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.AutomaticEvaluation.Parameterizer
AutomaticVisualization - Class in de.lmu.ifi.dbs.elki.result: Handler to process and visualize a Result.
AutomaticVisualization(String, VisualizerParameterizer, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.AutomaticVisualization: Constructor.
AutomaticVisualization.Parameterizer - Class in de.lmu.ifi.dbs.elki.result: Parameterization class.
AutomaticVisualization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.result.AutomaticVisualization.Parameterizer
autoopen - Variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler: Automatically open at the end
autoopen - Variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler.Parameterizer: Automatically open at the end
AUTOOPEN_ID - Static variable in class de.lmu.ifi.dbs.elki.result.KMLOutputHandler.Parameterizer: Parameter for automatically opening the output file.
AveragePrecisionAtK<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Evaluate a distance functions performance by computing the average precision at k, when ranking the objects by distance.
AveragePrecisionAtK(DistanceFunction<? super O>, int, double, RandomFactory, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.AveragePrecisionAtK: Constructor.
AveragePrecisionAtK.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Parameterization class.
AveragePrecisionAtK.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.AveragePrecisionAtK.Parameterizer
AveragePrecisionEvaluation - Class in de.lmu.ifi.dbs.elki.evaluation.scores: Evaluate using average precision.
AveragePrecisionEvaluation() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation
AveragePrecisionEvaluation.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.scores: Parameterization class.
AveragePrecisionEvaluation.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation.Parameterizer
averageSymmetricGini() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable: Compute the average Gini for each cluster (in both clusterings - symmetric).
avgDistance(Vector, DBIDs, Relation<V>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS: Computes the average distance of the objects to the centroid along the specified dimension.
axes - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: The distribution generators for each axis
AXIS - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Axis
AXIS_LABEL - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Axis label
AXIS_LABEL - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.ParallelAxisVisualization.Instance: Axis label class.
AXIS_TICK - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Axis tick
AXIS_TICK_MINOR - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Axis minor tick
AxisBasedReferencePoints - Class in de.lmu.ifi.dbs.elki.utilities.referencepoints: Strategy to pick reference points by placing them on the axis ends.
AxisBasedReferencePoints(double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.referencepoints.AxisBasedReferencePoints: Constructor.
AxisBasedReferencePoints.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.referencepoints: Parameterization class.
AxisBasedReferencePoints.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.referencepoints.AxisBasedReferencePoints.Parameterizer
axisProjection(int, int, int) - Static method in class de.lmu.ifi.dbs.elki.visualization.projections.AffineProjection: Compute an transformation matrix to show only axis ax1 and ax2.
AxisReorderVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Interactive SVG-Elements for reordering the axes.
AxisReorderVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisReorderVisualization: Constructor, adhering to
AxisReorderVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Instance for a particular plot.
AxisReorderVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisReorderVisualization.Instance: Constructor.
AxisVisibilityVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Layer for controlling axis visbility in parallel coordinates.
AxisVisibilityVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization: Constructor, adhering to
AxisVisibilityVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Instance for a particular data set.
AxisVisibilityVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AxisVisibilityVisualization.Instance: Constructor.
AxisVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot: Generates a SVG-Element containing axes, including labeling.
AxisVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AxisVisualization: Constructor.
AxisVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot: Instance.
AxisVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.AxisVisualization.Instance: Constructor.
axsep - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.AbstractParallelVisualization: Space between two axes


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