D-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

D

d - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier: Radius parameter d.
d - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier.Parameterizer: Query radius
d - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut: Set sizes, total and current iteration
d - Variable in class de.lmu.ifi.dbs.elki.data.VectorUtil.SortDBIDsBySingleDimension: Dimension to sort with.
d - Variable in class de.lmu.ifi.dbs.elki.data.VectorUtil.SortVectorsBySingleDimension: Dimension to sort with.
d - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition: Arrays for internal storage of eigenvalues.
D1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
D2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
D_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.AbstractDBOutlier.Parameterizer: Parameter to specify the size of the D-neighborhood
D_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.Parameterizer: Option ID for Epsilon parameter
d_max - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval: The maximum distance value.
d_min - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval: The minimum distance value.
d_zero - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC: Holds the value of DOC.Parameterizer.D_ZERO_ID.
d_zero - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC.Parameterizer: Stopping threshold for FastDOC.
D_ZERO_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC.Parameterizer: Stopping threshold for FastDOC.
DAFile - Class in de.lmu.ifi.dbs.elki.index.vafile: Dimension approximation file, a one-dimensional part of the PartialVAFile.
DAFile(Relation<? extends NumberVector>, int, int) - Constructor for class de.lmu.ifi.dbs.elki.index.vafile.DAFile: Constructor.
daFiles - Variable in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile: Partial VA files.
DashedLineStyleLibrary - Class in de.lmu.ifi.dbs.elki.visualization.style.lines: Line library using various dashed and dotted line styles.
DashedLineStyleLibrary(StyleLibrary) - Constructor for class de.lmu.ifi.dbs.elki.visualization.style.lines.DashedLineStyleLibrary: Constructor
dashnum - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.DashedLineStyleLibrary
dashpatterns - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.DashedLineStyleLibrary: Dash patterns to regularly use
data - Variable in class de.lmu.ifi.dbs.elki.data.VectorUtil.SortDBIDsBySingleDimension: The relation to sort.
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore: Data array
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore: Data array
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore: Data array
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore: Data array
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayStore: Data array.
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDRecordStore: Storage Map.
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDStore: Storage Map.
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapRecordStore: Storage Map.
data - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapStore: Storage Map.
data - Variable in class de.lmu.ifi.dbs.elki.database.ids.generic.MaskedDBIDs: Data storage.
data - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap: The actual data array.
data - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList: Distance values
data - Variable in class de.lmu.ifi.dbs.elki.datasource.ArrayAdapterDatabaseConnection: The actual data.
data - Variable in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleReader: Current object.
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleReader
data(int) - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.BundleStreamSource: Access a particular object and representation.
data(int, int) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle
data(int, int) - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.ObjectBundle: Access a particular object and representation.
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle: Get the value of the ith component.
data(int, int) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.StreamFromBundle
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.AbstractStreamConversionFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.DropNaNFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.NoMissingValuesFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.NoOpFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.selection.ByLabelFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.selection.RandomSamplingStreamFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ClassLabelFromPatternFilter
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.ClusteringVectorParser
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.NumberVectorLabelParser
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.SimplePolygonParser
data(int) - Method in class de.lmu.ifi.dbs.elki.datasource.parser.SimpleTransactionParser
data - Variable in class de.lmu.ifi.dbs.elki.math.geometry.XYCurve: X and Y positions
data - Variable in class de.lmu.ifi.dbs.elki.math.geometry.XYPlot.Curve: X and Y positions
data - Variable in class de.lmu.ifi.dbs.elki.parallel.variables.SharedDouble.Instance: Cache for last data consumed/produced
data - Variable in class de.lmu.ifi.dbs.elki.parallel.variables.SharedInteger.Instance: Cache for last data consumed/produced
data - Variable in class de.lmu.ifi.dbs.elki.parallel.variables.SharedObject.Instance: Cache for last data consumed/produced
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray: (Reused) store for numerical attributes.
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.MeanVarianceStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortStaticHistogram: Data store
data - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.ArrayListIter: The array list to iterate over.
data - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry: Registry data.
database - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering: Keeps the currently set database.
database - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHIntervalSplit: The database storing the parameterization functions.
Database - Interface in de.lmu.ifi.dbs.elki.database: Database specifies the requirements for any database implementation.
database - Variable in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.RelationObjectIterator: The database we use.
database - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.AbstractDBIDSimilarityFunction: The database we work on
database - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow: The database we use
database - Variable in class de.lmu.ifi.dbs.elki.workflow.InputStep: Holds the database to have the algorithms run with.
database - Variable in class de.lmu.ifi.dbs.elki.workflow.InputStep.Parameterizer: Holds the database to have the algorithms run on.
DATABASE_CONNECTION_ID - Static variable in class de.lmu.ifi.dbs.elki.database.AbstractDatabase.Parameterizer: Option to specify the data source for the database.
DATABASE_EMPTY - Static variable in interface de.lmu.ifi.dbs.elki.utilities.exceptions.ExceptionMessages: Messages in case a database is unexpectedly empty.
DATABASE_ID - Static variable in class de.lmu.ifi.dbs.elki.workflow.InputStep.Parameterizer: Option ID to specify the database type Key: -db
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.application.ClassifierHoldoutEvaluationTask: Holds the database connection to get the initial data from.
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.application.ClassifierHoldoutEvaluationTask.Parameterizer: Holds the database connection to get the initial data from.
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: The data source we get the initial data from.
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.database.HashmapDatabase.Parameterizer: Holds the database connection to get the initial data from.
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.database.StaticArrayDatabase: The data source we get the initial data from.
databaseConnection - Variable in class de.lmu.ifi.dbs.elki.database.StaticArrayDatabase.Parameterizer: Holds the database connection to get the initial data from.
DatabaseConnection - Interface in de.lmu.ifi.dbs.elki.datasource: DatabaseConnection is used to load data into a database.
DatabaseEventManager - Class in de.lmu.ifi.dbs.elki.database: Class to manage database events such as insertions and removals.
DatabaseEventManager() - Constructor for class de.lmu.ifi.dbs.elki.database.DatabaseEventManager
DatabaseEventManager.Type - Enum in de.lmu.ifi.dbs.elki.database: Types for aggregation.
DatabaseQuery - Interface in de.lmu.ifi.dbs.elki.database.query: General interface for database queries.
DatabaseTableModel() - Constructor for class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow.DatabaseTableModel
DatabaseUtil - Class in de.lmu.ifi.dbs.elki.utilities: Class with Database-related utility functions such as centroid computation, covariances etc.
DatabaseUtil() - Constructor for class de.lmu.ifi.dbs.elki.utilities.DatabaseUtil: Fake constructor: Do not instantiate!
dataLength() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle
dataLength() - Method in interface de.lmu.ifi.dbs.elki.datasource.bundle.ObjectBundle: Get the number of objects contained.
dataLength() - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.SingleObjectBundle
DATALINE - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.BoundingBoxVisualization.Instance: Generic tags to indicate the type of element.
DATALINE - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.LineVisualization.Instance: Generic tags to indicate the type of element.
dataListenerList - Variable in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: Holds the listeners for data store changes
dataProjections(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution: Returns the data vectors after projection.
DataStore<T> - Interface in de.lmu.ifi.dbs.elki.database.datastore: Generic storage interface for objects indexed by DBID.
DataStoreEvent - Class in de.lmu.ifi.dbs.elki.database.datastore: Encapsulates information describing changes, i.e. updates, insertions, and / or deletions in a DataStore, and used to notify all subscribed DataStoreListener of the change.
DataStoreEvent(DBIDs, DBIDs, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreEvent: Constructor.
DataStoreFactory - Interface in de.lmu.ifi.dbs.elki.database.datastore: API for a storage factory used for producing larger storage maps.
DataStoreIDMap - Interface in de.lmu.ifi.dbs.elki.database.datastore: Interface to map DBIDs to integer record ids for use in storage.
DataStoreListener - Interface in de.lmu.ifi.dbs.elki.database.datastore: Defines the interface for an object that listens to changes in a DataStore.
dataStoreObjects - Variable in class de.lmu.ifi.dbs.elki.database.DatabaseEventManager: The objects that were changed in the current DataStoreEvent.
DataStoreUtil - Class in de.lmu.ifi.dbs.elki.database.datastore: Storage utility class.
DataStoreUtil() - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil
DataStoreUtil.AscendingByDoubleDataStore - Class in de.lmu.ifi.dbs.elki.database.datastore: Sort objects by a double relation
DataStoreUtil.DescendingByDoubleDataStore - Class in de.lmu.ifi.dbs.elki.database.datastore: Sort objects by a double relation
dataVector(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution: Returns the data vectors after projection.
db - Variable in class de.lmu.ifi.dbs.elki.application.jsmap.JSONWebServer: The database we use for obtaining object bundles.
db - Variable in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.CollectionFromRelation: The database we query.
dbgStyle - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane: Debug message style
DBID - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Database IDs.
DBID - Interface in de.lmu.ifi.dbs.elki.database.ids: Database ID object.
DBIDArrayIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Array iterators that can also go backwards and seek.
DBIDArrayMIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Modifiable array iterator.
DBIDDataStore - Interface in de.lmu.ifi.dbs.elki.database.datastore: DBID-valued data store (avoids boxing/unboxing).
DBIDDistanceFunction - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction: Distance functions valid in a database context only (i.e. for DBIDs) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.
DBIDDistanceQuery - Class in de.lmu.ifi.dbs.elki.database.query.distance: Run a distance query based on DBIDs
DBIDDistanceQuery(Relation<DBID>, DBIDDistanceFunction) - Constructor for class de.lmu.ifi.dbs.elki.database.query.distance.DBIDDistanceQuery: Constructor.
DBIDFactory - Interface in de.lmu.ifi.dbs.elki.database.ids: Factory interface for generating DBIDs.
DBIDIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Iterator for DBIDs.
DBIDItr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.generic.MaskedDBIDs.DBIDItr: Constructor.
DBIDMIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Modifiable DBID iterator.
DBIDPair - Interface in de.lmu.ifi.dbs.elki.database.ids: Immutable pair of two DBIDs.
DBIDRange - Interface in de.lmu.ifi.dbs.elki.database.ids: Static DBID range.
DBIDRangeDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource: This is a fake datasource that produces a static DBID range only.
DBIDRangeDatabaseConnection(int, int) - Constructor for class de.lmu.ifi.dbs.elki.datasource.DBIDRangeDatabaseConnection: Constructor.
DBIDRangeDatabaseConnection.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource: Parameterization class.
DBIDRangeDistanceFunction - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction: Distance functions valid in a static database context only (i.e. for DBIDRanges) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.
DBIDRangeDistanceQuery - Class in de.lmu.ifi.dbs.elki.database.query.distance: Run a distance query based on DBIDRanges
DBIDRangeDistanceQuery(Relation<DBID>, DBIDRangeDistanceFunction) - Constructor for class de.lmu.ifi.dbs.elki.database.query.distance.DBIDRangeDistanceQuery: Constructor.
DBIDRef - Interface in de.lmu.ifi.dbs.elki.database.ids: Some object referencing a DBID.
DBIDRefIter - Interface in de.lmu.ifi.dbs.elki.evaluation.scores.adapter: A score iterator wrapping a DBIDRef object.
DBIDS - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Database ID lists.
DBIDs - Interface in de.lmu.ifi.dbs.elki.database.ids: Interface for a collection of database references (IDs).
dbids - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow: The DBIDs to display
DBIDSelection - Class in de.lmu.ifi.dbs.elki.result: Class representing selected Database-IDs and/or a selection range.
DBIDSelection(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.result.DBIDSelection: Constructor with new object IDs.
DBIDSimilarityFunction - Interface in de.lmu.ifi.dbs.elki.distance.similarityfunction: Interface DBIDSimilarityFunction describes the requirements of any similarity function defined over object IDs.
DBIDsTest - Class in de.lmu.ifi.dbs.elki.evaluation.scores.adapter: Test predicate using a DBID set as positive elements.
DBIDsTest(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DBIDsTest: Constructor.
DBIDUtil - Class in de.lmu.ifi.dbs.elki.database.ids: DBID Utility functions.
DBIDUtil() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Static - no public constructor.
DBIDVar - Interface in de.lmu.ifi.dbs.elki.database.ids: (Persistent) variable storing a DBID reference.
DBIDView - Class in de.lmu.ifi.dbs.elki.database.relation: Pseudo-representation that is the object ID itself.
DBIDView(DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.database.relation.DBIDView: Constructor.
DBOutlierDetection<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Simple distanced based outlier detection algorithm.
DBOutlierDetection(DistanceFunction<O>, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierDetection: Constructor with actual parameters.
DBOutlierDetection.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Parameterization class.
DBOutlierScore<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Compute percentage of neighbors in the given neighborhood with size d.
DBOutlierScore(DistanceFunction<O>, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierScore: Constructor with parameters.
DBOutlierScore.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Parameterization class.
DBSCAN<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Density-Based Clustering of Applications with Noise (DBSCAN), an algorithm to find density-connected sets in a database.
DBSCAN(DistanceFunction<? super O>, double, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN: Constructor with parameters.
DBSCAN.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Parameterization class.
dbsize - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch: Database size.
de.lmu.ifi.dbs.elki - package de.lmu.ifi.dbs.elki: ELKI framework "Environment for Developing KDD-Applications Supported by Index-Structures".
de.lmu.ifi.dbs.elki.algorithm - package de.lmu.ifi.dbs.elki.algorithm: Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.benchmark - package de.lmu.ifi.dbs.elki.algorithm.benchmark: Benchmarking pseudo algorithms.
de.lmu.ifi.dbs.elki.algorithm.classification - package de.lmu.ifi.dbs.elki.algorithm.classification: Classification algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering - package de.lmu.ifi.dbs.elki.algorithm.clustering: Clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation - package de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Affinity Propagation (AP) clustering.
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering - package de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering: Biclustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation - package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation: Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash - package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash: Helper classes for the CASH algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.em - package de.lmu.ifi.dbs.elki.algorithm.clustering.em: Expectation-Maximization clustering algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan - package de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: Generalized DBSCAN.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical - package de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction - package de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction: Extraction of partitional clusterings from hierarchical results.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans - package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans: K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization - package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization: Initialization strategies for k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel - package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel: Parallelized implementations of k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality - package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality: Quality measures for k-Means results.
de.lmu.ifi.dbs.elki.algorithm.clustering.meta - package de.lmu.ifi.dbs.elki.algorithm.clustering.meta: Meta clustering algorithms, that get their result from other clusterings or external sources.
de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional - package de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional: Clustering algorithms for one-dimensional data.
de.lmu.ifi.dbs.elki.algorithm.clustering.optics - package de.lmu.ifi.dbs.elki.algorithm.clustering.optics: OPTICS family of clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace - package de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique - package de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique: Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial - package de.lmu.ifi.dbs.elki.algorithm.clustering.trivial: Trivial clustering algorithms: all in one, no clusters, label clusterings These methods are mostly useful for providing a reference result in evaluation.
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain - package de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain: Clustering algorithms for uncertain data.
de.lmu.ifi.dbs.elki.algorithm.itemsetmining - package de.lmu.ifi.dbs.elki.algorithm.itemsetmining: Algorithms for frequent itemset mining such as APRIORI.
de.lmu.ifi.dbs.elki.algorithm.outlier - package de.lmu.ifi.dbs.elki.algorithm.outlier: Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased - package de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased: Angle-based outlier detection algorithms.
de.lmu.ifi.dbs.elki.algorithm.outlier.clustering - package de.lmu.ifi.dbs.elki.algorithm.outlier.clustering: Clustering based outlier detection.
de.lmu.ifi.dbs.elki.algorithm.outlier.distance - package de.lmu.ifi.dbs.elki.algorithm.outlier.distance: Distance-based outlier detection algorithms, such as DBOutlier and kNN.
de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel - package de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel: Parallel implementations of distance-based outlier detectors.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof - package de.lmu.ifi.dbs.elki.algorithm.outlier.lof: LOF family of outlier detection algorithms.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel - package de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel: Parallelized variants of LOF.
de.lmu.ifi.dbs.elki.algorithm.outlier.meta - package de.lmu.ifi.dbs.elki.algorithm.outlier.meta: Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial - package de.lmu.ifi.dbs.elki.algorithm.outlier.spatial: Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood - package de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood: Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted - package de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted: Weighted Neighborhood definitions.
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace - package de.lmu.ifi.dbs.elki.algorithm.outlier.subspace: Subspace outlier detection methods.
de.lmu.ifi.dbs.elki.algorithm.outlier.svm - package de.lmu.ifi.dbs.elki.algorithm.outlier.svm: Support-Vector-Machines for outlier detection.
de.lmu.ifi.dbs.elki.algorithm.outlier.trivial - package de.lmu.ifi.dbs.elki.algorithm.outlier.trivial: Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
de.lmu.ifi.dbs.elki.algorithm.statistics - package de.lmu.ifi.dbs.elki.algorithm.statistics: Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application - package de.lmu.ifi.dbs.elki.application: Base classes for stand alone applications.
de.lmu.ifi.dbs.elki.application.cache - package de.lmu.ifi.dbs.elki.application.cache: Utility applications for the persistence layer such as distance cache builders.
de.lmu.ifi.dbs.elki.application.experiments - package de.lmu.ifi.dbs.elki.application.experiments: Packaged experiments to make them easy to reproduce.
de.lmu.ifi.dbs.elki.application.geo - package de.lmu.ifi.dbs.elki.application.geo: Application for exploring geo data.
de.lmu.ifi.dbs.elki.application.greedyensemble - package de.lmu.ifi.dbs.elki.application.greedyensemble: Greedy ensembles for outlier detection.
de.lmu.ifi.dbs.elki.application.internal - package de.lmu.ifi.dbs.elki.application.internal: Internal utilities for development.
de.lmu.ifi.dbs.elki.application.jsmap - package de.lmu.ifi.dbs.elki.application.jsmap: JavaScript based map client - server architecture.
de.lmu.ifi.dbs.elki.data - package de.lmu.ifi.dbs.elki.data: Basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.data.model - package de.lmu.ifi.dbs.elki.data.model: Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.data.projection - package de.lmu.ifi.dbs.elki.data.projection: Data projections.
de.lmu.ifi.dbs.elki.data.spatial - package de.lmu.ifi.dbs.elki.data.spatial: Spatial data types - interfaces and utilities.
de.lmu.ifi.dbs.elki.data.synthetic - package de.lmu.ifi.dbs.elki.data.synthetic: Generators for synthetic data sets
de.lmu.ifi.dbs.elki.data.synthetic.bymodel - package de.lmu.ifi.dbs.elki.data.synthetic.bymodel: Generator using a distribution model specified in an XML configuration file.
de.lmu.ifi.dbs.elki.data.type - package de.lmu.ifi.dbs.elki.data.type: Data type information, also used for type restrictions.
de.lmu.ifi.dbs.elki.data.uncertain - package de.lmu.ifi.dbs.elki.data.uncertain: Uncertain data objects.
de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier - package de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier: Classes to generate uncertain objects from existing certain data.
de.lmu.ifi.dbs.elki.database - package de.lmu.ifi.dbs.elki.database: ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.datastore - package de.lmu.ifi.dbs.elki.database.datastore: General data store layer API (along the lines of Map<DBID, T> - use everywhere!)
de.lmu.ifi.dbs.elki.database.datastore.memory - package de.lmu.ifi.dbs.elki.database.datastore.memory: Memory data store implementation for ELKI.
de.lmu.ifi.dbs.elki.database.ids - package de.lmu.ifi.dbs.elki.database.ids: Database object identification and ID group handling API.
de.lmu.ifi.dbs.elki.database.ids.generic - package de.lmu.ifi.dbs.elki.database.ids.generic: Database object identification and ID group handling - generic implementations.
de.lmu.ifi.dbs.elki.database.ids.integer - package de.lmu.ifi.dbs.elki.database.ids.integer: Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
de.lmu.ifi.dbs.elki.database.query - package de.lmu.ifi.dbs.elki.database.query: Database queries - computing distances, neighbors, similarities - API and general documentation.
de.lmu.ifi.dbs.elki.database.query.distance - package de.lmu.ifi.dbs.elki.database.query.distance: Prepared queries for distances.
de.lmu.ifi.dbs.elki.database.query.knn - package de.lmu.ifi.dbs.elki.database.query.knn: Prepared queries for k nearest neighbor (kNN) queries.
de.lmu.ifi.dbs.elki.database.query.range - package de.lmu.ifi.dbs.elki.database.query.range: Prepared queries for ε-range queries, that return all objects within the radius ε.
de.lmu.ifi.dbs.elki.database.query.rknn - package de.lmu.ifi.dbs.elki.database.query.rknn: Prepared queries for reverse k nearest neighbor (rkNN) queries.
de.lmu.ifi.dbs.elki.database.query.similarity - package de.lmu.ifi.dbs.elki.database.query.similarity: Prepared queries for similarity functions.
de.lmu.ifi.dbs.elki.database.relation - package de.lmu.ifi.dbs.elki.database.relation: Relations, materialized and virtual (views).
de.lmu.ifi.dbs.elki.datasource - package de.lmu.ifi.dbs.elki.datasource: Data normalization (and reconstitution) of data sets.
de.lmu.ifi.dbs.elki.datasource.bundle - package de.lmu.ifi.dbs.elki.datasource.bundle: Object bundles - exchange container for multi-represented objects.
de.lmu.ifi.dbs.elki.datasource.filter - package de.lmu.ifi.dbs.elki.datasource.filter: Data filtering, in particular for normalization and projection.
de.lmu.ifi.dbs.elki.datasource.filter.cleaning - package de.lmu.ifi.dbs.elki.datasource.filter.cleaning: Filters for data cleaning.
de.lmu.ifi.dbs.elki.datasource.filter.normalization - package de.lmu.ifi.dbs.elki.datasource.filter.normalization: Data normalization.
de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise - package de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise: Normalizations operating on columns / variates; where each column is treated independently.
de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise - package de.lmu.ifi.dbs.elki.datasource.filter.normalization.instancewise: Instancewise normalization, where each instance is normalized independently.
de.lmu.ifi.dbs.elki.datasource.filter.selection - package de.lmu.ifi.dbs.elki.datasource.filter.selection: Filters for selecting and sorting data to process.
de.lmu.ifi.dbs.elki.datasource.filter.transform - package de.lmu.ifi.dbs.elki.datasource.filter.transform: Data space transformations.
de.lmu.ifi.dbs.elki.datasource.filter.typeconversions - package de.lmu.ifi.dbs.elki.datasource.filter.typeconversions: Filters to perform data type conversions.
de.lmu.ifi.dbs.elki.datasource.parser - package de.lmu.ifi.dbs.elki.datasource.parser: Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.distance - package de.lmu.ifi.dbs.elki.distance: distance functions and similarity functions.
de.lmu.ifi.dbs.elki.distance.distancefunction - package de.lmu.ifi.dbs.elki.distance.distancefunction: Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter - package de.lmu.ifi.dbs.elki.distance.distancefunction.adapter: Distance functions deriving distances from e.g. similarity measures
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram - package de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram: Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation - package de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.external - package de.lmu.ifi.dbs.elki.distance.distancefunction.external: Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.geo - package de.lmu.ifi.dbs.elki.distance.distancefunction.geo: Geographic (earth) distance functions.
de.lmu.ifi.dbs.elki.distance.distancefunction.histogram - package de.lmu.ifi.dbs.elki.distance.distancefunction.histogram: Distance functions for one-dimensional histograms.
de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski - package de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski: Minkowski space L_p norms such as the popular Euclidean and Manhattan distances.
de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic - package de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic: Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence.
de.lmu.ifi.dbs.elki.distance.distancefunction.set - package de.lmu.ifi.dbs.elki.distance.distancefunction.set: Distance functions for binary and set type data.
de.lmu.ifi.dbs.elki.distance.distancefunction.strings - package de.lmu.ifi.dbs.elki.distance.distancefunction.strings: Distance functions for strings.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace - package de.lmu.ifi.dbs.elki.distance.distancefunction.subspace: Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries - package de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Distance functions designed for time series.
de.lmu.ifi.dbs.elki.distance.similarityfunction - package de.lmu.ifi.dbs.elki.distance.similarityfunction: Similarity functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster - package de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster: Similarity measures for comparing clusters.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel - package de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel: Kernel functions.
de.lmu.ifi.dbs.elki.evaluation - package de.lmu.ifi.dbs.elki.evaluation: Functionality for the evaluation of algorithms.
de.lmu.ifi.dbs.elki.evaluation.classification - package de.lmu.ifi.dbs.elki.evaluation.classification: Evaluation of classification algorithms.
de.lmu.ifi.dbs.elki.evaluation.classification.holdout - package de.lmu.ifi.dbs.elki.evaluation.classification.holdout: Holdout and cross-validation strategies for evaluating classifiers.
de.lmu.ifi.dbs.elki.evaluation.clustering - package de.lmu.ifi.dbs.elki.evaluation.clustering: Evaluation of clustering results.
de.lmu.ifi.dbs.elki.evaluation.clustering.internal - package de.lmu.ifi.dbs.elki.evaluation.clustering.internal: Internal evaluation measures for clusterings.
de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments - package de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments: Pair-segment analysis of multiple clusterings.
de.lmu.ifi.dbs.elki.evaluation.histogram - package de.lmu.ifi.dbs.elki.evaluation.histogram: Functionality for the evaluation of algorithms using histograms.
de.lmu.ifi.dbs.elki.evaluation.index - package de.lmu.ifi.dbs.elki.evaluation.index: Simple index evaluation methods
de.lmu.ifi.dbs.elki.evaluation.outlier - package de.lmu.ifi.dbs.elki.evaluation.outlier: Evaluate an outlier score using a misclassification based cost model.
de.lmu.ifi.dbs.elki.evaluation.scores - package de.lmu.ifi.dbs.elki.evaluation.scores: Evaluation of rankings and scorings.
de.lmu.ifi.dbs.elki.evaluation.scores.adapter - package de.lmu.ifi.dbs.elki.evaluation.scores.adapter: Adapter classes for ranking and scoring measures.
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix - package de.lmu.ifi.dbs.elki.evaluation.similaritymatrix: Render a distance matrix to visualize a clustering-distance-combination.
de.lmu.ifi.dbs.elki.gui - package de.lmu.ifi.dbs.elki.gui: Graphical User Interfaces for ELKI
de.lmu.ifi.dbs.elki.gui.configurator - package de.lmu.ifi.dbs.elki.gui.configurator: Configurator components
de.lmu.ifi.dbs.elki.gui.icons - package de.lmu.ifi.dbs.elki.gui.icons: Icons for ELKI GUI.
de.lmu.ifi.dbs.elki.gui.minigui - package de.lmu.ifi.dbs.elki.gui.minigui: A very simple UI to build ELKI command lines.
de.lmu.ifi.dbs.elki.gui.multistep - package de.lmu.ifi.dbs.elki.gui.multistep: Multi-step GUI for ELKI
de.lmu.ifi.dbs.elki.gui.multistep.panels - package de.lmu.ifi.dbs.elki.gui.multistep.panels: Panels for the multi-step GUI
de.lmu.ifi.dbs.elki.gui.util - package de.lmu.ifi.dbs.elki.gui.util: Utility classes for GUIs (e.g. a class to display a logging panel)
de.lmu.ifi.dbs.elki.index - package de.lmu.ifi.dbs.elki.index: Index structure implementations
de.lmu.ifi.dbs.elki.index.distancematrix - package de.lmu.ifi.dbs.elki.index.distancematrix: Precomputed distance matrix.
de.lmu.ifi.dbs.elki.index.idistance - package de.lmu.ifi.dbs.elki.index.idistance: iDistance is a distance based indexing technique, using a reference points embedding.
de.lmu.ifi.dbs.elki.index.invertedlist - package de.lmu.ifi.dbs.elki.index.invertedlist: Indexes using inverted lists.
de.lmu.ifi.dbs.elki.index.lsh - package de.lmu.ifi.dbs.elki.index.lsh: Locality Sensitive Hashing
de.lmu.ifi.dbs.elki.index.lsh.hashfamilies - package de.lmu.ifi.dbs.elki.index.lsh.hashfamilies: Hash function families for LSH.
de.lmu.ifi.dbs.elki.index.lsh.hashfunctions - package de.lmu.ifi.dbs.elki.index.lsh.hashfunctions: Hash functions for LSH
de.lmu.ifi.dbs.elki.index.preprocessed - package de.lmu.ifi.dbs.elki.index.preprocessed: Index structure based on preprocessors
de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics - package de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics: Preprocessed index used by the FastOPTICS algorithm.
de.lmu.ifi.dbs.elki.index.preprocessed.knn - package de.lmu.ifi.dbs.elki.index.preprocessed.knn: Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca - package de.lmu.ifi.dbs.elki.index.preprocessed.localpca: Index using a preprocessed local PCA.
de.lmu.ifi.dbs.elki.index.preprocessed.preference - package de.lmu.ifi.dbs.elki.index.preprocessed.preference: Indexes storing preference vectors.
de.lmu.ifi.dbs.elki.index.preprocessed.snn - package de.lmu.ifi.dbs.elki.index.preprocessed.snn: Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.projected - package de.lmu.ifi.dbs.elki.index.projected: Projected indexes for data.
de.lmu.ifi.dbs.elki.index.tree - package de.lmu.ifi.dbs.elki.index.tree: Tree-based index structures
de.lmu.ifi.dbs.elki.index.tree.metrical - package de.lmu.ifi.dbs.elki.index.tree.metrical: Tree-based index structures for metrical vector spaces.
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree - package de.lmu.ifi.dbs.elki.index.tree.metrical.covertree: Cover-tree variations.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants: M-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees: Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp: MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop: MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax: MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab: MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree: MTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query: Classes for performing queries (knn, range, ...) on metrical trees.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies: Strategies for M-Trees (and variants).
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.insert: Insertion (choose path) strategies of nodes in an M-Tree (and variants).
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split - package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split: Splitting strategies of nodes in an M-Tree (and variants).
de.lmu.ifi.dbs.elki.index.tree.query - package de.lmu.ifi.dbs.elki.index.tree.query: Classes related to generic tree queries.
de.lmu.ifi.dbs.elki.index.tree.spatial - package de.lmu.ifi.dbs.elki.index.tree.spatial: Tree-based index structures for spatial indexing.
de.lmu.ifi.dbs.elki.index.tree.spatial.kd - package de.lmu.ifi.dbs.elki.index.tree.spatial.kd: K-d-tree and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants: R*-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat: FlatRStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query: Queries on the R-Tree family of indexes: kNN and range queries.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn: RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar: RStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies: Various strategies for R-Trees and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.bulk: Packages for bulk-loading R*-Trees.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert: Insertion strategies for R-Trees
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.overflow - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.overflow: Overflow treatment strategies for R-Trees
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert: Reinsertion strategies for R-Trees
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split: Splitting strategies for R-Trees
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util - package de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util: Utilities for R*-Tree and variants.
de.lmu.ifi.dbs.elki.index.vafile - package de.lmu.ifi.dbs.elki.index.vafile: Vector Approximation File
de.lmu.ifi.dbs.elki.logging - package de.lmu.ifi.dbs.elki.logging: Logging facility for controlling logging behavior of the complete framework.
de.lmu.ifi.dbs.elki.logging.progress - package de.lmu.ifi.dbs.elki.logging.progress: Progress status objects (for UI)
de.lmu.ifi.dbs.elki.logging.statistics - package de.lmu.ifi.dbs.elki.logging.statistics: Classes for logging various statistics.
de.lmu.ifi.dbs.elki.math - package de.lmu.ifi.dbs.elki.math: Mathematical operations and utilities used throughout the framework.
de.lmu.ifi.dbs.elki.math.analysis - package de.lmu.ifi.dbs.elki.math.analysis: Analysis package
de.lmu.ifi.dbs.elki.math.dimensionsimilarity - package de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Functions to compute the similarity of dimensions (or the interestingness of the combination).
de.lmu.ifi.dbs.elki.math.geodesy - package de.lmu.ifi.dbs.elki.math.geodesy
de.lmu.ifi.dbs.elki.math.geometry - package de.lmu.ifi.dbs.elki.math.geometry: Algorithms from computational geometry.
de.lmu.ifi.dbs.elki.math.linearalgebra - package de.lmu.ifi.dbs.elki.math.linearalgebra: Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.math.linearalgebra.fitting - package de.lmu.ifi.dbs.elki.math.linearalgebra.fitting: Function to numerically fit a function (such as a Gaussian distribution to given data.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca - package de.lmu.ifi.dbs.elki.math.linearalgebra.pca: Principal Component Analysis (PCA) and Eigenvector processing.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions - package de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions: Weight functions used in weighted PCA via WeightedCovarianceMatrixBuilder
de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections - package de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections: Random projection families.
de.lmu.ifi.dbs.elki.math.random - package de.lmu.ifi.dbs.elki.math.random: Random number generation.
de.lmu.ifi.dbs.elki.math.scales - package de.lmu.ifi.dbs.elki.math.scales: Scales handling for plotting.
de.lmu.ifi.dbs.elki.math.spacefillingcurves - package de.lmu.ifi.dbs.elki.math.spacefillingcurves: Space filling curves.
de.lmu.ifi.dbs.elki.math.statistics - package de.lmu.ifi.dbs.elki.math.statistics: Statistical tests and methods.
de.lmu.ifi.dbs.elki.math.statistics.dependence - package de.lmu.ifi.dbs.elki.math.statistics.dependence: Statistical measures of dependence, such as correlation.
de.lmu.ifi.dbs.elki.math.statistics.distribution - package de.lmu.ifi.dbs.elki.math.statistics.distribution: Standard distributions, with random generation functionalities.
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator - package de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Estimators for statistical distributions.
de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta - package de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta: Meta estimators: estimators that do not actually estimate themselves, but instead use other estimators, e.g. on a trimmed data set, or as an ensemble.
de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality - package de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality: Methods for estimating the intrinsic dimensionality.
de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions - package de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions: Kernel functions from statistics.
de.lmu.ifi.dbs.elki.math.statistics.tests - package de.lmu.ifi.dbs.elki.math.statistics.tests: Statistical tests.
de.lmu.ifi.dbs.elki.parallel - package de.lmu.ifi.dbs.elki.parallel: Parallel processing core for ELKI.
de.lmu.ifi.dbs.elki.parallel.processor - package de.lmu.ifi.dbs.elki.parallel.processor: Processor API of ELKI, and some essential shared processors.
de.lmu.ifi.dbs.elki.parallel.variables - package de.lmu.ifi.dbs.elki.parallel.variables: Variables are instantiated for each thread, and allow passing values from one processor to another within the same thread.
de.lmu.ifi.dbs.elki.persistent - package de.lmu.ifi.dbs.elki.persistent: Persistent data management.
de.lmu.ifi.dbs.elki.result - package de.lmu.ifi.dbs.elki.result: Result types, representation and handling
de.lmu.ifi.dbs.elki.result.outlier - package de.lmu.ifi.dbs.elki.result.outlier: Outlier result classes
de.lmu.ifi.dbs.elki.result.textwriter - package de.lmu.ifi.dbs.elki.result.textwriter: Text serialization (CSV, Gnuplot, Console, ...)
de.lmu.ifi.dbs.elki.result.textwriter.naming - package de.lmu.ifi.dbs.elki.result.textwriter.naming: Naming schemes for clusters (for output when an algorithm doesn't generate cluster names).
de.lmu.ifi.dbs.elki.result.textwriter.writers - package de.lmu.ifi.dbs.elki.result.textwriter.writers: Serialization handlers for individual data types.
de.lmu.ifi.dbs.elki.utilities - package de.lmu.ifi.dbs.elki.utilities: Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.utilities.datastructures - package de.lmu.ifi.dbs.elki.utilities.datastructures: Basic memory structures such as heaps and object hierarchies.
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike - package de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
de.lmu.ifi.dbs.elki.utilities.datastructures.arrays - package de.lmu.ifi.dbs.elki.utilities.datastructures.arrays: Utilities for arrays: advanced sorting for primitvie arrays.
de.lmu.ifi.dbs.elki.utilities.datastructures.hash - package de.lmu.ifi.dbs.elki.utilities.datastructures.hash: Hashing based data structures.
de.lmu.ifi.dbs.elki.utilities.datastructures.heap - package de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Heap structures and variations such as bounded priority heaps.
de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy - package de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy: Delegate implementation of a hierarchy.
de.lmu.ifi.dbs.elki.utilities.datastructures.histogram - package de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Classes for computing histograms.
de.lmu.ifi.dbs.elki.utilities.datastructures.iterator - package de.lmu.ifi.dbs.elki.utilities.datastructures.iterator: ELKI Iterator API.
de.lmu.ifi.dbs.elki.utilities.documentation - package de.lmu.ifi.dbs.elki.utilities.documentation: Documentation utilities: Annotations for Title, Description, Reference
de.lmu.ifi.dbs.elki.utilities.ensemble - package de.lmu.ifi.dbs.elki.utilities.ensemble: Utility classes for simple ensembles.
de.lmu.ifi.dbs.elki.utilities.exceptions - package de.lmu.ifi.dbs.elki.utilities.exceptions: Exception classes and common exception messages.
de.lmu.ifi.dbs.elki.utilities.io - package de.lmu.ifi.dbs.elki.utilities.io: Utility classes for input/output.
de.lmu.ifi.dbs.elki.utilities.optionhandling - package de.lmu.ifi.dbs.elki.utilities.optionhandling: Parameter handling and option descriptions.
de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints - package de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints: Constraints allow to restrict possible values for parameters.
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization - package de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization: Configuration managers See the de.lmu.ifi.dbs.elki.utilities.optionhandling package for documentation!
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters - package de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters: Classes for various typed parameters.
de.lmu.ifi.dbs.elki.utilities.pairs - package de.lmu.ifi.dbs.elki.utilities.pairs: Pairs utility classes.
de.lmu.ifi.dbs.elki.utilities.referencepoints - package de.lmu.ifi.dbs.elki.utilities.referencepoints: Package containing strategies to obtain reference points Shared code for various algorithms that use reference points.
de.lmu.ifi.dbs.elki.utilities.scaling - package de.lmu.ifi.dbs.elki.utilities.scaling: Scaling functions: linear, logarithmic, gamma, clipping, ...
de.lmu.ifi.dbs.elki.utilities.scaling.outlier - package de.lmu.ifi.dbs.elki.utilities.scaling.outlier: Scaling of Outlier scores, that require a statistical analysis of the occurring values
de.lmu.ifi.dbs.elki.utilities.xml - package de.lmu.ifi.dbs.elki.utilities.xml: XML and XHTML utilities.
de.lmu.ifi.dbs.elki.visualization - package de.lmu.ifi.dbs.elki.visualization: Visualization package of ELKI.
de.lmu.ifi.dbs.elki.visualization.batikutil - package de.lmu.ifi.dbs.elki.visualization.batikutil: Commonly used functionality useful for Apache Batik.
de.lmu.ifi.dbs.elki.visualization.colors - package de.lmu.ifi.dbs.elki.visualization.colors: Color scheme handling for ELKI.
de.lmu.ifi.dbs.elki.visualization.css - package de.lmu.ifi.dbs.elki.visualization.css: Managing CSS styles / classes.
de.lmu.ifi.dbs.elki.visualization.gui - package de.lmu.ifi.dbs.elki.visualization.gui: Package to provide a visualization GUI.
de.lmu.ifi.dbs.elki.visualization.gui.detail - package de.lmu.ifi.dbs.elki.visualization.gui.detail: Classes for managing a detail view.
de.lmu.ifi.dbs.elki.visualization.gui.overview - package de.lmu.ifi.dbs.elki.visualization.gui.overview: Classes for managing the overview plot.
de.lmu.ifi.dbs.elki.visualization.opticsplot - package de.lmu.ifi.dbs.elki.visualization.opticsplot: Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.projections - package de.lmu.ifi.dbs.elki.visualization.projections: Visualization projections
de.lmu.ifi.dbs.elki.visualization.projector - package de.lmu.ifi.dbs.elki.visualization.projector: Projectors are responsible for finding appropriate projections for data relations.
de.lmu.ifi.dbs.elki.visualization.savedialog - package de.lmu.ifi.dbs.elki.visualization.savedialog: Save dialog for SVG plots.
de.lmu.ifi.dbs.elki.visualization.style - package de.lmu.ifi.dbs.elki.visualization.style: Style management for ELKI visualizations.
de.lmu.ifi.dbs.elki.visualization.style.lines - package de.lmu.ifi.dbs.elki.visualization.style.lines: Generate line styles for plotting in CSS
de.lmu.ifi.dbs.elki.visualization.style.marker - package de.lmu.ifi.dbs.elki.visualization.style.marker: Draw plot markers
de.lmu.ifi.dbs.elki.visualization.svg - package de.lmu.ifi.dbs.elki.visualization.svg: Base SVG functionality (generation, markers, thumbnails, export, ...).
de.lmu.ifi.dbs.elki.visualization.visualizers - package de.lmu.ifi.dbs.elki.visualization.visualizers: Visualizers for various results
de.lmu.ifi.dbs.elki.visualization.visualizers.actions - package de.lmu.ifi.dbs.elki.visualization.visualizers.actions: Action-only "visualizers" that only produce menu entries.
de.lmu.ifi.dbs.elki.visualization.visualizers.histogram - package de.lmu.ifi.dbs.elki.visualization.visualizers.histogram: Visualizers based on 1D projected histograms.
de.lmu.ifi.dbs.elki.visualization.visualizers.optics - package de.lmu.ifi.dbs.elki.visualization.visualizers.optics: Visualizers that do work on OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments - package de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments: Visualizers for inspecting cluster differences using pair counting segments.
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel - package de.lmu.ifi.dbs.elki.visualization.visualizers.parallel: Visualizers based on parallel coordinates.
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster - package de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.cluster: Visualizers for clustering results based on parallel coordinates.
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.index - package de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.index: Visualizers for index structure based on parallel coordinates.
de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection - package de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection: Visualizers for object selection based on parallel projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot: Visualizers based on scatterplots.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster: Visualizers for clustering results based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density: Visualizers for data set density in a scatterplot projection.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index: Visualizers for index structures based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier: Visualizers for outlier scores based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection: Visualizers for object selection based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain - package de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain: Visualizers for uncertain data.
de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs - package de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs: Thumbnail "Visualizers" (that take care of refreshing thumbnails)
de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj - package de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Visualizers that do not use a particular projection.
de.lmu.ifi.dbs.elki.workflow - package de.lmu.ifi.dbs.elki.workflow: Work flow packages, e.g. following the usual KDD model, closely related to CRISP-DM
deallocateDBIDRange(DBIDRange) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory: Deallocate a static DBID range.
deallocateDBIDRange(DBIDRange) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Deallocate a static DBID range.
deallocateDBIDRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ReusingDBIDFactory
deallocateDBIDRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.SimpleDBIDFactory
deallocateDBIDRange(DBIDRange) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TrivialDBIDFactory
deallocateSingleDBID(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory: Return a single DBID for reuse.
deallocateSingleDBID(DBID) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Return a single DBID for reuse.
deallocateSingleDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ReusingDBIDFactory
deallocateSingleDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.SimpleDBIDFactory
deallocateSingleDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.TrivialDBIDFactory
dearrange(Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.AbstractSimpleProjection: Undo the rearrangement of components.
dearrange(Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.Simple1D
dearrange(Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.Simple2D
debug(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'fine' debugging level.
debug(CharSequence) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'fine' debugging level.
DEBUG - Static variable in class de.lmu.ifi.dbs.elki.logging.LoggingConfiguration: General debug flag.
DEBUG_ID - Static variable in class de.lmu.ifi.dbs.elki.application.AbstractApplication.Parameterizer: Optional Parameter to specify a class to enable debugging for.
DEBUG_LAYOUT - Static variable in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot: Draw red borders around items.
debugDumpCandidates(StringBuilder, List<? extends Itemset>, VectorFieldTypeInformation<BitVector>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.APRIORI: Debug method: output all itemsets.
debugExtraCheckSymmetry - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix: Debug flag, to double-check all write operations.
debugExtraCheckSymmetry - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheFloatDistanceInOnDiskMatrix: Debug flag, to double-check all write operations.
debugFine(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'fine' debugging level.
debugFine(CharSequence) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'fine' debugging level.
debugFiner(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'finer' debugging level.
debugFiner(CharSequence) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'finer' debugging level.
debugFinest(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'finest' debugging level.
debugFinest(CharSequence) - Method in class de.lmu.ifi.dbs.elki.logging.Logging: Log a message at the 'finest' debugging level.
debugformat - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane: Formatter for debugging messages
debugformat - Variable in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler: Formatter for debugging messages
debugHull() - Method in class de.lmu.ifi.dbs.elki.math.geometry.SweepHullDelaunay2D: Debug helper
decoder - Variable in class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil.StringSerializer: Decoder.
DecreasingVectorIter - Class in de.lmu.ifi.dbs.elki.evaluation.scores.adapter: Class to iterate over a number vector in decreasing order.
DecreasingVectorIter(NumberVector) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DecreasingVectorIter: Constructor.
decrement() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.AtomicLongCounter
decrement() - Method in interface de.lmu.ifi.dbs.elki.logging.statistics.Counter: Decrement the counter.
decrement() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.UnsynchronizedLongCounter
def - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore: Default value.
DEFAULT - Static variable in class de.lmu.ifi.dbs.elki.math.random.RandomFactory: Global default factory
DEFAULT - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Default
DEFAULT_ALPHA - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO: The default value for HiCO.Parameterizer.ALPHA_ID.
DEFAULT_ALPHA - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex.Factory: The default value for alpha.
DEFAULT_ALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PercentageEigenPairFilter: The default value for alpha.
DEFAULT_APPLICATION - Static variable in class de.lmu.ifi.dbs.elki.application.ELKILauncher: Application to run by default.
DEFAULT_ARFF_MAGIC_CLASS - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Pattern to auto-convert columns to class labels.
DEFAULT_ARFF_MAGIC_EID - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Pattern to auto-convert columns to external ids.
DEFAULT_BINS - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.histogram.ColoredHistogramVisualizer: Number of bins to use in histogram.
DEFAULT_BUTTON_COLOR - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGButton: Default button color
DEFAULT_DEGREE - Static variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction: The default degree.
DEFAULT_DELTA - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings.Parameterizer: The default value for delta.
DEFAULT_DELTA - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO: The default value for HiCO.Parameterizer.DELTA_ID.
DEFAULT_DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter: The default value for delta.
DEFAULT_DISTANCE_FUNCTION - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTreeFactory: The default distance function.
DEFAULT_ENABLEVIS - Static variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer: Default pattern for visualizer enabling.
DEFAULT_ENSEMBLE_DEPTH - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer: Default number of clusterings to run.
DEFAULT_EPSILON - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory: The default value for epsilon.
DEFAULT_FORMAT - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat: Default CSV input format.
DEFAULT_INITIAL_CAPACITY - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.Heap: Default initial capacity.
DEFAULT_PALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.ProgressiveEigenPairFilter: The default value for alpha.
DEFAULT_PATTERN - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.ByLabelOutlier: The default pattern to use.
DEFAULT_PREFIX - Static variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.PrettyMarkers: Default prefix to use.
DEFAULT_PROPERTIES_EXTENSION - Static variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary: File extension
DEFAULT_PROPERTIES_PATH - Static variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary: Default properties path
DEFAULT_QUALITY - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Default JPEG quality setting
DEFAULT_RALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.RelativeEigenPairFilter: The default value for ralpha.
DEFAULT_SAMPLE_SIZE - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.AbstractDiscreteUncertainifier.Parameterizer: Default sample size for generating finite representations.
DEFAULT_SCHEME_FILENAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary: File name of the default color scheme.
DEFAULT_SCHEME_NAME - Static variable in class de.lmu.ifi.dbs.elki.visualization.style.PropertiesBasedStyleLibrary: Name of the default color scheme.
DEFAULT_SEPARATOR - Static variable in class de.lmu.ifi.dbs.elki.data.HierarchicalClassLabel: The default separator pattern, a point ('.').
DEFAULT_SEPARATOR - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.CSVReaderFormat: A pattern defining whitespace.
DEFAULT_SEPARATOR_STRING - Static variable in class de.lmu.ifi.dbs.elki.data.HierarchicalClassLabel: The default separator, a point ('.').
DEFAULT_STRATEGY - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory: Default strategy.
DEFAULT_TEXT_COLOR - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGButton: Default text color
DEFAULT_THRESHOLD - Static variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer: Default threshold for resizing.
DEFAULT_TITLE - Static variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultVisualizer: Default title
DEFAULT_TITLE - Static variable in class de.lmu.ifi.dbs.elki.visualization.savedialog.SVGSaveDialog: The default title.
DEFAULT_TRY_LIMIT - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.AbstractUncertainObject: Default retry limit for sampling, to guard against bad parameters.
default_visibility - Variable in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask: Flag to signal default visibility of a visualizer.
DEFAULT_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.DropEigenPairFilter: The default value for walpha.
DEFAULT_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.ProgressiveEigenPairFilter: The default value for alpha.
DEFAULT_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.SignificantEigenPairFilter: The default value for walpha.
DEFAULT_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.WeakEigenPairFilter: The default value for walpha.
defaultHandlers - Static variable in class de.lmu.ifi.dbs.elki.workflow.OutputStep
DefaultPageHeader - Class in de.lmu.ifi.dbs.elki.persistent: Default implementation of a page header.
DefaultPageHeader() - Constructor for class de.lmu.ifi.dbs.elki.persistent.DefaultPageHeader: Empty constructor for serialization.
DefaultPageHeader(int) - Constructor for class de.lmu.ifi.dbs.elki.persistent.DefaultPageHeader: Creates a new header with the specified parameters.
defaultpath - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.FileNameEditor: Default path.
defaultValue - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter: The default value of the parameter (may be null).
defaultValueTaken - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.AbstractParameter: Specifies if the default value of this parameter was taken as parameter value.
defbg - Variable in class de.lmu.ifi.dbs.elki.gui.util.TreePopup.Renderer: Colors
deffg - Variable in class de.lmu.ifi.dbs.elki.gui.util.TreePopup.Renderer: Colors
defineBicluster(BitSet, BitSet) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering: Defines a Bicluster as given by the included rows and columns.
defineBicluster(long[], long[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.AbstractBiclustering: Defines a Bicluster as given by the included rows and columns.
defs - Variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Definitions element of the document.
DEG2RAD - Static variable in class de.lmu.ifi.dbs.elki.math.MathUtil: Constant for degrees to radians.
deg2rad(double) - Static method in class de.lmu.ifi.dbs.elki.math.MathUtil: Convert Degree to Radians.
degree - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction: Degree of the polynomial kernel function.
degree - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction.Parameterizer: Degree of the polynomial kernel function.
DEGREE_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction.Parameterizer: Degree parameter.
delaunay - Variable in class de.lmu.ifi.dbs.elki.math.geometry.AlphaShape: Delaunay triangulation
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore.StorageAccessor
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDBIDStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDoubleStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDIntegerStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDRecordStore.StorageAccessor
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDStore
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapRecordStore.StorageAccessor
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapStore
delete(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore: Delete the contents for a particular ID and notifies the registered listeners.
delete(DBIDs) - Method in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: Removes the objects from the database (by calling HashmapDatabase.doDelete(DBIDRef) for each object) and indexes and fires a deletion event.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: Removes the object from the database (by calling HashmapDatabase.doDelete(DBIDRef) ) and indexes and fires a deletion event.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.relation.MaterializedDoubleRelation: Delete an objects values.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.relation.MaterializedRelation: Delete an objects values.
delete(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.relation.ModifiableRelation: Delete an objects values.
delete(DBIDs) - Method in interface de.lmu.ifi.dbs.elki.database.UpdatableDatabase: Removes and returns the specified objects with the given ids from the database.
delete(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.UpdatableDatabase: Removes and returns the specified objects with the given ids from the database.
delete(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.index.DynamicIndex: Deletes the specified object from this index.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeIndex: Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex: Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeIndex: Deletes the specified object from this index.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeIndex: Deletes the specified object from this index.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree: Deletes the specified object from this index.
delete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTreeIndex: Deletes the specified object from this index.
deleteAll(DBIDs) - Method in interface de.lmu.ifi.dbs.elki.index.DynamicIndex: Deletes the specified objects from this index.
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTreeIndex: Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex: Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeIndex
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeIndex
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree
deleteAll(DBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar.RStarTreeIndex
deleteAllEntries() - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Deletes all entries in this node.
deleteButton - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow: Button to delete the selected objects
deleteChildren(Element) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance: Delete the children of the element
deleteChildren(Element) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance: Delete the children of the element
deleteChildren(Element) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance: Delete the children of the element
deleteChildren(Element) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance: Delete the children of the element.
deleteChildren(Element) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance: Delete the children of the element
deleteEntry(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode: Deletes the entry at the specified index and shifts all entries after the index to left.
deleteEntry(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat.FlatRStarTreeNode: Deletes the entry at the specified index and shifts all entries after the index to left.
deleteNode(N) - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTree: Delete a node from the backing storage.
deletePage(int) - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractStoringPageFile: Deletes the node with the specified id from this file.
deletePage(int) - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCache
deletePage(int) - Method in class de.lmu.ifi.dbs.elki.persistent.MemoryPageFile
deletePage(int) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile: Deletes the node with the specified id from this file.
deletePage(int) - Method in interface de.lmu.ifi.dbs.elki.persistent.PageFile: Deletes the node with the specified id from this file.
deletePage(int) - Method in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile: Deletes the node with the specified id from this file.
deletePath(IndexTreePath<E>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree: Delete a leaf at a given path - deletions for non-leaves are not supported!
DeLiClu<NV extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: DeliClu: Density-Based Hierarchical Clustering, a hierarchical algorithm to find density-connected sets in a database.
DeLiClu(DistanceFunction<? super NV>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu: Constructor.
DeLiClu.Parameterizer<NV extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: Parameterization class.
DeLiClu.SpatialObjectPair - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: Encapsulates an entry in the cluster order.
DeLiCluDirectoryEntry - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Defines the requirements for a directory entry in an DeLiClu-Tree node.
DeLiCluDirectoryEntry() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluDirectoryEntry: Empty constructor for serialization purposes.
DeLiCluDirectoryEntry(int, ModifiableHyperBoundingBox, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluDirectoryEntry: Constructs a new DeLiCluDirectoryEntry object with the given parameters.
DeLiCluEntry - Interface in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Defines the requirements for an entry in an DeLiClu-Tree node.
DeLiCluLeafEntry - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Defines the requirements for a leaf entry in an DeLiClu-Tree node.
DeLiCluLeafEntry() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluLeafEntry: Empty constructor for serialization purposes.
DeLiCluLeafEntry(DBID, NumberVector) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluLeafEntry: Constructs a new LeafEntry object with the given parameters.
DeLiCluNode - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Represents a node in a DeLiClu-Tree.
DeLiCluNode() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluNode: Empty constructor for Externalizable interface.
DeLiCluNode(int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluNode: Creates a new DeLiCluNode with the specified parameters.
DeLiCluTree - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: DeLiCluTree is a spatial index structure based on an R-Tree.
DeLiCluTree(PageFile<DeLiCluNode>, AbstractRTreeSettings) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree: Constructor.
DeLiCluTreeFactory<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Factory for DeLiClu R*-Trees.
DeLiCluTreeFactory(PageFileFactory<?>, AbstractRTreeSettings) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeFactory: Constructor.
DeLiCluTreeFactory.Parameterizer<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: Parameterization class.
DeLiCluTreeIndex<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu: The common use of the DeLiClu tree: indexing number vectors.
DeLiCluTreeIndex(Relation<O>, PageFile<DeLiCluNode>, AbstractRTreeSettings) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeIndex: Constructor.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch: Threshold for the score.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: Threshold for the score (ChengAndChurch.Parameterizer.DELTA_ID).
DELTA - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: A small number to handle numbers near 0 as 0.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings: Parameter to specify the threshold for approximate linear dependency: the strong eigenvectors of q are approximately linear dependent from the strong eigenvectors p if the following condition holds for all strong eigenvectors q_i of q (lambda_q < lambda_p): q_i' * M^check_p * q_i <= delta^2, must be a double equal to or greater than 0.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings: Delta parameter, for selecting strong Eigenvectors.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO: Delta parameter
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Parameterizer: Delta parameter
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM: Delta parameter
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM.Parameterizer: Stopping threshold
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings: The threshold for small eigenvalues.
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF: The radii changing ratio
delta - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF.Parameterizer: Radius increase factor.
delta(double, double) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction: Compute the delta of two values.
delta - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction: Delta parameter, similarity threshold for attributes.
delta(double, double) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction
delta - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction.Parameterizer: Delta parameter, similarity threshold for attributes.
delta(double, double) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction
DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: A small number to handle numbers near 0 as 0.
delta - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter: Threshold for strong eigenpairs, can be absolute or relative.
delta - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter.Parameterizer: Threshold for strong eigenpairs, can be absolute or relative.
DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: A small number to handle numbers near 0 as 0.
delta - Variable in class de.lmu.ifi.dbs.elki.math.scales.LinearScale: Scale delta := max - min
DELTA - Static variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.MixtureModelOutlierScalingFunction: Convergence parameter
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: Threshold value to determine the maximal acceptable score (mean squared residue) of a bicluster.
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings.Parameterizer: Parameter to specify the threshold for approximate linear dependency: the strong eigenvectors of q are approximately linear dependent from the strong eigenvectors p if the following condition holds for all strong eigenvectors q_i of q (lambda_q < lambda_p): q_i' * M^check_p * q_i <= delta^2, must be a double equal to or greater than 0.
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Parameterizer: Parameter to specify the threshold of a distance between a vector q and a given space that indicates that q adds a new dimension to the space, must be a double equal to or greater than 0.
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM.Parameterizer: Parameter to specify the termination criterion for maximization of E(M): E(M) - E(M') < em.delta, must be a double equal to or greater than 0.
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings.Parameterizer: Parameter Delta: maximum variance allowed
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF.Parameterizer: Option ID for radius increases
DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction.Parameterizer: DELTA parameter
deltaparams - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod
deltasq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate: Squared delta value.
DendrogramModel - Class in de.lmu.ifi.dbs.elki.data.model: Model for dendrograms, provides the distance to the child cluster.
DendrogramModel(double) - Constructor for class de.lmu.ifi.dbs.elki.data.model.DendrogramModel: Constructor.
denormalizeValue(double) - Method in class de.lmu.ifi.dbs.elki.math.MeanVariance: Return the unnormalized value (centered at the mean, distance normalized by standard deviation)
dens - Variable in class de.lmu.ifi.dbs.elki.math.statistics.KernelDensityEstimator: Result storage: density
densecols - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.DropNaNFilter: Columns to check.
densecols - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter: Columns to check.
DenseItemset - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining: APRIORI itemset.
DenseItemset(long[], int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset: Constructor.
denseUnits - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace: The dense units belonging to this subspace.
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.BiweightKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.CosineKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.GaussianKernelDensityFunction
density(double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.KernelDensityFunction: Density contribution of a point at the given relative distance delta >= 0.
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriangularKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TricubeKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.TriweightKernelDensityFunction
density(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.UniformKernelDensityFunction
densitycorrection - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: Correction factor for probability computation
DensityEstimationOverlay - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density: A simple density estimation visualization, based on a simple kernel-density in the projection, not the actual data!
DensityEstimationOverlay() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density.DensityEstimationOverlay: Constructor.
DensityEstimationOverlay.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density: Instance for a particular data set.
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
dependence(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, A) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
dependence(NumberArrayAdapter<?, A>, List<? extends A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.CorrelationDependenceMeasure
dependence(NumberArrayAdapter<?, A>, List<? extends A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.CorrelationDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.dependence.DependenceMeasure: Measure the dependence of two variables.
dependence(NumberArrayAdapter<?, A>, A, A) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.dependence.DependenceMeasure: Measure the dependence of two variables.
dependence(NumberArrayAdapter<?, A>, List<? extends A>) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.dependence.DependenceMeasure: Measure the dependence of two variables.
dependence(double[], double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.dependence.DependenceMeasure: Measure the dependence of two variables.
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure
dependence(NumberArrayAdapter<?, A>, List<? extends A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HiCSDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HoeffdingsDDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HSMDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.JensenShannonEquiwidthDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.MCEDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.MutualInformationEquiwidthDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.SlopeDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.SlopeInversionDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.SpearmanCorrelationDependenceMeasure
dependence(NumberArrayAdapter<?, A>, A, NumberArrayAdapter<?, B>, B) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.SURFINGDependenceMeasure
DependenceMeasure - Interface in de.lmu.ifi.dbs.elki.math.statistics.dependence: Measure the dependence of two variables.
DEPENDENCY_DERIVATOR_RANDOM_SAMPLE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.DependencyDerivator: Flag to use random sample (use knn query around centroid, if flag is not set).
DependencyDerivator<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm: Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.
DependencyDerivator(NumberVectorDistanceFunction<? super V>, NumberFormat, PCAFilteredRunner, int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.DependencyDerivator: Constructor.
dependencyDerivator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.SimpleCOP: Holds the object performing the dependency derivation
DependencyDerivator.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm: Parameterization class.
depth - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction.TempCluster: Current height.
depth() - Method in class de.lmu.ifi.dbs.elki.data.HierarchicalClassLabel: The length of the hierarchy of names.
depth - Variable in class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters.Node
deref(DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Dereference a DBID reference.
derivative(int, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DerivativeDTWDistanceFunction: Given a NumberVector and the position of an element, approximates the gradient of given element.
DerivativeDTWDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Derivative Dynamic Time Warping distance for numerical vectors.
DerivativeDTWDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DerivativeDTWDistanceFunction: Constructor.
DerivativeDTWDistanceFunction(double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DerivativeDTWDistanceFunction: Constructor.
DerivedComparator() - Constructor for class de.lmu.ifi.dbs.elki.result.OrderingFromDataStore.DerivedComparator
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.EmptyParameterization: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.MergedParameterization
descend(Object) - Method in interface de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.SerializedParameterization: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.TrackParameters: Descend parameterization tree into sub-option.
descend(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.UnParameterization
DescendingByDoubleDataStore(DoubleDataStore) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByDoubleDataStore: Constructor.
DescendingByDoubleRelation(DoubleRelation) - Constructor for class de.lmu.ifi.dbs.elki.database.relation.RelationUtil.DescendingByDoubleRelation: Constructor.
describeParameterizable(StringBuilder, Class<?>, int, String) - Static method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionUtil: Format a description of a Parameterizable (including recursive options).
description() - Method in enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate: Descriptions of the aggregate values.
Description - Annotation Type in de.lmu.ifi.dbs.elki.utilities.documentation: Class/algorithm description
description - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID: The description of the OptionID.
DESCRIPTION_ID - Static variable in class de.lmu.ifi.dbs.elki.application.AbstractApplication.Parameterizer: Optional Parameter to specify a class to obtain a description for.
deselectAllSegments() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.SegmentsStylingPolicy: Deselect all currently selected segments
deselectSegment(Segment) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.SegmentsStylingPolicy: Deselect a segment
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDBIDStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayRecordStore.StorageAccessor
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDBIDStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDoubleStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDIntegerStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDRecordStore.StorageAccessor
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDStore
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapRecordStore.StorageAccessor
destroy() - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapStore
destroy() - Method in interface de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore: Deallocate the storage, freeing the memory and notifies the registered listeners.
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Remove the listeners
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView: Cleanup function.
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot: Destroy this overview plot.
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.AbstractVisualization
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeMBRVisualization.Instance
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization.Instance
destroy() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs.ThumbnailVisualization
destroy() - Method in interface de.lmu.ifi.dbs.elki.visualization.visualizers.Visualization: Destroy the visualization.
destroyToNaiveMatrix() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix: Obtain the covariance matrix according to the population statistics: n degrees of freedom.
destroyToSampleMatrix() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix: Obtain the covariance matrix according to the sample statistics: (n-1) degrees of freedom.
destroyVisualizations() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Destination (minimum) size of the structure.
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram: Destination (minimum) size of the structure.
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatDynamicHistogram: Destination (minimum) size of the structure.
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntDynamicHistogram: Destination (minimum) size of the structure.
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongDynamicHistogram: Destination (minimum) size of the structure.
destsize - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortDynamicHistogram: Destination (minimum) size of the structure.
det() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LUDecomposition: Determinant
det() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Matrix determinant
detachPlot(SVGPlot) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.JSVGSynchronizedCanvas: Execute the detaching event.
DetailView - Class in de.lmu.ifi.dbs.elki.visualization.gui.detail: Manages a detail view.
DetailView(VisualizerContext, PlotItem, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView: Constructor.
DetailViewSelectedEvent - Class in de.lmu.ifi.dbs.elki.visualization.gui.overview: Event when a particular subplot was selected.
DetailViewSelectedEvent(OverviewPlot, int, String, int, PlotItem) - Constructor for class de.lmu.ifi.dbs.elki.visualization.gui.overview.DetailViewSelectedEvent: Constructor.
determineAlphaMax(int, double[], HyperBoundingBox) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Determines the n-th alpha value where this function has a maximum in the specified interval.
determineAlphaMin(int, double[], HyperBoundingBox) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Determines the n-th alpha value where this function has a minimum in the specified interval.
determineAlphaMinMax(HyperBoundingBox) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Determines the alpha values where this function has a minumum and maximum value in the given interval.
determineBasis(double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Determines a basis defining a subspace described by the specified alpha values.
determineClusters() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace: Determines all clusters in this subspace by performing a depth-first search algorithm to find connected dense units.
determineClusters(List<CLIQUESubspace<V>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.CLIQUE: Determines the clusters in the specified dense subspaces.
determineGlobalExtremum() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Determines the global extremum of this parameterization function.
determineGlobalExtremumType() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction: Determines the type of the global extremum.
determineIDs(DBIDs, HyperBoundingBox, double, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHIntervalSplit: Determines the ids belonging to the given interval, i.e. the parameterization functions falling within the interval.
determineLowerAndUpperHull(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ConvexHull: Computes the lower and upper hull of the specified distances.
determineMinMaxDistance(Relation<ParameterizationFunction>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Determines the minimum and maximum function value of all parameterization functions stored in the specified database.
determineNextIntervalAtMaxLevel(ObjectHeap<IntegerPriorityObject<CASHInterval>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Determines the next ''best'' interval at maximum level, i.e. the next interval containing the most unprocessed objects.
determinePreferenceVector(Relation<V>, ModifiableDBIDs[], StringBuilder) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex: Determines the preference vector according to the specified neighbor ids.
determinePreferenceVector(Relation<V>, DBIDRef, DBIDs, StringBuilder) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex: Determines the preference vector according to the specified neighbor ids.
determinePreferenceVectorByApriori(Relation<V>, ModifiableDBIDs[], StringBuilder) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex: Determines the preference vector with the apriori strategy.
determinePreferenceVectorByMaxIntersection(ModifiableDBIDs[], StringBuilder) - Method in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex: Determines the preference vector with the max intersection strategy.
DEV_MAX_ID - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier.Parameterizer: Parameter for maximum 3-sigma deviation.
DEV_MAX_ID - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.UniformUncertainifier.Parameterizer: Maximum deviation of the generated bounding box.
DEV_MIN_ID - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.SimpleGaussianUncertainifier.Parameterizer: Parameter for minimum 3-sigma deviation.
DEV_MIN_ID - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.uncertainifier.UniformUncertainifier.Parameterizer: Minimum deviation of the generated bounding box.
devianceTerm(double, double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.PoissonDistribution: Evaluate the deviance term of the saddle point approximation.
deviation(Vector, Matrix) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.LMCLUS: Deviation from a manifold described by beta.
deviation(double[], double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.tests.GoodnessOfFitTest: Measure the deviation of a full sample from a conditional sample.
deviation(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.tests.KolmogorovSmirnovTest
deviation(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.tests.StandardizedTwoSampleAndersonDarlingTest
deviation(double[][]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.tests.StandardizedTwoSampleAndersonDarlingTest: K-samples version of the Anderson-Darling test.
deviation(double[], double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.tests.WelchTTest
dfs(CLIQUEUnit<V>, ModifiableDBIDs, CLIQUESubspace<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUESubspace: Depth-first search algorithm to find connected dense units in this subspace that build a cluster.
diagonal(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Returns a quadratic Matrix consisting of zeros and of the given values on the diagonal.
diagonal(Vector) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Returns a quadratic Matrix consisting of zeros and of the given values on the diagonal.
diagonal(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath: Returns a quadratic Matrix consisting of zeros and of the given values on the diagonal.
DiagonalGaussianModel - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em: Simpler model for a single Gaussian cluster, without covariances.
DiagonalGaussianModel(double, Vector) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel: Constructor.
DiagonalGaussianModel(double, Vector, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel: Constructor.
DiagonalGaussianModelFactory<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em: Factory for EM with multivariate gaussian models using diagonal matrixes.
DiagonalGaussianModelFactory(KMeansInitialization<V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModelFactory: Constructor.
DiagonalGaussianModelFactory.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em: Parameterization class
DIALOG_ERROR - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
DIALOG_INFORMATION - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
DIALOG_WARNING - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
diameter - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.HilbertFeatures: Data space diameter
difference(DBIDs, DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil: Returns the difference of the two specified collection of IDs.
digamma(double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution: Compute the Psi / Digamma function Reference: J.
DIGITS_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.TooltipScoreVisualization.Parameterizer: Parameter for the gamma-correction.
dim - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional.KNNKernelDensityMinimaClustering: Dimension to use for clustering.
dim - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional.KNNKernelDensityMinimaClustering.Parameterizer: Dimension to use for clustering.
dim - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch: Database dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.KernelDensityEstimator: Dimensionality of data set
dim - Variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators: Benchmark parameters.
dim - Variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer: Benchmark parameters.
dim - Variable in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMaxComparator: Current dimension.
dim - Variable in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMeanComparator: Current dimension.
dim - Variable in class de.lmu.ifi.dbs.elki.data.spatial.SpatialSingleMinComparator: Current dimension.
dim - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: The dimensionality
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter: Desired dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter.Parameterizer: Desired dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Adapter: Dimension to process.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Adapter: Dimension to process.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.IntegerRankTieNormalization.Sorter: Dimension to use for sorting.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.GlobalPrincipalComponentAnalysisTransform: Actual dataset dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.RandomDoubleVectorDatabaseConnection: Dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.datasource.RandomDoubleVectorDatabaseConnection.Parameterizer: Dimensionality.
dim - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction: The dimension to be considered for distance computation.
dim - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction.Parameterizer: Selected dimension.
dim() - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.AbstractVectorIter: Get the dimension in the original vector.
dim(int) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix: Get the dimension at position idx.
dim(int) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.FullDimensionSimilarityMatrix
dim(int) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix
dim - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.AffineTransformation: the dimensionality of the transformation
dim - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner.Cand: Dimensionality
dim - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance: Dimension.
dim1 - Variable in class de.lmu.ifi.dbs.elki.visualization.projections.Simple2D: Dimensions for fast projection mode.
dim2 - Variable in class de.lmu.ifi.dbs.elki.visualization.projections.Simple2D: Dimensions for fast projection mode.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional.KNNKernelDensityMinimaClustering.Parameterizer: Dimension to use for clustering.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer: Dimensionality.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform.Parameterizer: Desired dimensionality.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.UncertainSplitFilter.Parameterizer: Parameter for specifying the number of dimensions of the sample.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.RandomDoubleVectorDatabaseConnection.Parameterizer: Database to specify the random vector dimensionality.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction.Parameterizer: Parameter for dimensionality.
DIM_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.Factory.Parameterizer: Parameter for choosing the number of dimensions to use for each curve.
DIM_P - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.VectorDimensionalityFilter.Parameterizer: Parameter for specifying the dimensionality.
dimension - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique.CLIQUEInterval: The dimension of this interval in the (original) data space.
dimension - Variable in class de.lmu.ifi.dbs.elki.data.model.DimensionModel: Number of dimensions
dimension - Variable in class de.lmu.ifi.dbs.elki.index.vafile.DAFile: Dimension of this approximation file.
dimensionality(Relation<ParameterizationFunction>) - Static method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Get the dimensionality of a vector field.
dimensionality(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate.Instance: Get the correlation dimensionality of a single object.
dimensionality(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Instance: Get the correlation dimensionality of a single object.
dimensionality(Relation<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS: Ugly hack to allow using this implementation without having a well-defined dimensionality.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.BitVector: Dimensionality of this bit vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.projection.FeatureSelection: Output dimensionality.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.projection.RandomProjection: Output dimensionality.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.projection.RandomProjection.Parameterizer: Output dimensionality.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.SparseByteVector: The dimensionality of this feature vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.SparseDoubleVector: The dimensionality of this feature vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.SparseFloatVector: The dimensionality of this feature vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector: The dimensionality of this feature vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.SparseShortVector: The dimensionality of this feature vector.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.data.Subspace: The dimensionality of this subspace.
dimensionality() - Method in class de.lmu.ifi.dbs.elki.data.Subspace: Returns the dimensionality of this subspace.
dimensionality(Relation<? extends SpatialComparable>) - Static method in class de.lmu.ifi.dbs.elki.database.relation.RelationUtil: Get the dimensionality of a database relation.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.PerturbationFilter: Stores the dimensionality from the preprocessing.
dimensionality(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction: Get the common dimensionality of the two objects.
dimensionality(SpatialComparable, SpatialComparable, int) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction: Get the common dimensionality of the two objects.
dimensionality(NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction: Get the common dimensionality of the two objects.
dimensionality(NumberVector, NumberVector, int) - Static method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction: Get the common dimensionality of the two objects.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split: Dimensionality.
dimensionality - Variable in class de.lmu.ifi.dbs.elki.math.spacefillingcurves.ZCurveTransformer: Dimensionality.
dimensionality(Relation<?>) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.ParallelPlotFactory
dimensionality(Relation<?>) - Method in class de.lmu.ifi.dbs.elki.visualization.projector.ScatterPlotFactory
DIMENSIONALITY_ID - Static variable in class de.lmu.ifi.dbs.elki.data.projection.RandomProjection.Parameterizer: Parameter for the desired output dimensionality.
DimensionComparator() - Constructor for class de.lmu.ifi.dbs.elki.data.Subspace.DimensionComparator
dimensionIsRelevant(int, Relation<V>, DBIDs) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC: Utility method to test if a given dimension is relevant as determined via a set of reference points (i.e. if the variance along the attribute is lower than the threshold).
DimensionModel - Class in de.lmu.ifi.dbs.elki.data.model: Cluster model just providing a cluster dimensionality.
DimensionModel(int) - Constructor for class de.lmu.ifi.dbs.elki.data.model.DimensionModel: Constructor
dimensions - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.ClusterCandidate: Selected dimensions
dimensions - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.PROCLUSCluster: The correlated dimensions of this cluster.
dimensions - Variable in class de.lmu.ifi.dbs.elki.data.Subspace: The dimensions building this subspace.
dimensions - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction: The dimensions to be considered for distance computation.
dimensions - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction.Parameterizer: Bitmask of the dimensions
DimensionSelectingLatLngDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.geo: Distance function for 2D vectors in Latitude, Longitude form.
DimensionSelectingLatLngDistanceFunction(int, int, EarthModel) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction: Constructor.
DimensionSelectingLatLngDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.geo: Parameterization class.
DimensionSelectingSubspaceDistanceFunction<O> - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace: Interface for dimension selecting subspace distance functions.
DimensionSimilarity<V> - Interface in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Interface for computing pairwise dimension similarities, used for arranging dimensions in parallel coordinate plots.
DimensionSimilarityMatrix - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Class representing a similarity matrix between dimensions.
DimensionSimilarityMatrix(int) - Constructor for class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix: Constructor.
DimensionSimilarityMatrix.FullDimensionSimilarityMatrix - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Complete matrix of pairwise dimension similarities.
DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Partial matrix of pairwise dimension similarities.
DimensionSimilarityMatrix.PrimAdapter - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Adapter class for running prim's algorithm.
dimensonsToString() - Method in class de.lmu.ifi.dbs.elki.data.Subspace: Returns a string representation of the dimensions of this subspace separated by comma.
dimensonsToString(String) - Method in class de.lmu.ifi.dbs.elki.data.Subspace: Returns a string representation of the dimensions of this subspace.
dimi - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.DoubleIntInt
dimj - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.DoubleIntInt
dimlat - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction: Latitude dimension.
dimlat - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction.Parameterizer: Latitude dimension.
dimlng - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction: Longitude dimension.
dimlng - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction.Parameterizer: Longitude dimension.
dimOrder - Variable in class de.lmu.ifi.dbs.elki.visualization.projections.SimpleParallel: Ordering of dimensions
dims - Variable in class de.lmu.ifi.dbs.elki.data.projection.FeatureSelection.Parameterizer: Dimensions to select.
dims - Variable in class de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection: Subspace.
dims - Variable in class de.lmu.ifi.dbs.elki.data.projection.NumericalFeatureSelection.Parameterizer: Dimensions to select.
dims - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.SplitNumberVectorFilter: Selected dimensions.
dims - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.SplitNumberVectorFilter.Parameterizer: Dimensions to use.
dims - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.UncertainSplitFilter: Data dimensionality.
dims - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.UncertainSplitFilter.Parameterizer: Field to hold the dimensional constraint.
dims - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree: The number of dimensions.
dims - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree: The number of dimensions.
dims - Variable in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.FullDimensionSimilarityMatrix: Number of dimensions.
dims - Variable in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix: Enumeration of dimensions to use (so we could use a subset only!)
dims - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.ProjectedCentroid: The selected dimensions.
dims - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.randomprojections.RandomSubsetProjectionFamily.SubsetProjection: Input dimensions.
DIMS_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction.Parameterizer: Dimensions parameter.
DIR_STRATEGY_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy.Parameterizer: Insertion strategy for directory nodes.
dirCapacity - Variable in class de.lmu.ifi.dbs.elki.index.tree.IndexTree: The capacity of a directory node (= 1 + maximum number of entries in a directory node).
dirCapacity - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexHeader: The capacity of a directory node (= 1 + maximum number of entries in a directory node).
DirClassIterator(File) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator: Constructor from Directory
Direction() - Constructor for enum de.lmu.ifi.dbs.elki.visualization.svg.SVGArrow.Direction
DirectoryEntry - Interface in de.lmu.ifi.dbs.elki.index.tree: Directory Entry
dirMinimum - Variable in class de.lmu.ifi.dbs.elki.index.tree.IndexTree: The minimum number of entries in a directory node.
dirMinimum - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexHeader: The minimum number of entries in a directory node.
dirStrategy - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy: Strategy when inserting into directory nodes
dirStrategy - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.insert.CombinedInsertionStrategy.Parameterizer: Strategy when inserting into directory nodes
dirty - Variable in class de.lmu.ifi.dbs.elki.persistent.AbstractExternalizablePage: The dirty flag of this page.
disable - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores: Pattern for disabling (skipping) methods.
disable - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores.Parameterizer: Pattern for disabling (skipping) methods.
DISABLE_REFINE_FLAG - Static variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.Factory.Parameterizer: Option ID for disabling refinement.
disableInteractions - Variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Flag whether Batik interactions should be disabled.
disableStart() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Disable capturing of 'mousedown' events.
disableStop() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Disable capturing of 'mousemove' and 'mouseup' events.
DISBALE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores.Parameterizer: Option ID for disabling methods.
discarded - Variable in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.GeneratorSingleCluster: Discarded count
DiscardResultHandler - Class in de.lmu.ifi.dbs.elki.result: A dummy result handler that discards the actual result, for use in benchmarks.
DiscardResultHandler() - Constructor for class de.lmu.ifi.dbs.elki.result.DiscardResultHandler: Default constructor.
disconnect() - Method in class de.lmu.ifi.dbs.elki.parallel.ParallelCore: Disconnect to the executor.
DISCRETE_UNCERTAIN_OBJECT - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Uncertain objects.
DiscreteUncertainObject - Interface in de.lmu.ifi.dbs.elki.data.uncertain: Interface for discrete uncertain objects, that are represented by a finite (possibly weighted) number of samples.
discretize(NumberArrayAdapter<?, A>, A, int, int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure: Discretize a data set into equi-width bin numbers.
DiSH<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Algorithm for detecting subspace hierarchies.
DiSH(double, int, DiSHPreferenceVectorIndex.Factory<V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH: Constructor.
DiSH.DiSHClusterOrder - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: DiSH cluster order.
DiSH.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: OPTICS variant used by DiSH internally.
DiSH.Instance.Sorter - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Sort new candidates by their distance, for determining the core size.
DiSH.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Parameterization class.
DiSHClusterOrder(String, String, ArrayModifiableDBIDs, WritableDoubleDataStore, WritableDBIDDataStore, WritableIntegerDataStore, WritableDataStore<long[]>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.DiSHClusterOrder: Constructor.
DiSHPreferenceVectorIndex<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Preprocessor for DiSH preference vector assignment to objects of a certain database.
DiSHPreferenceVectorIndex(Relation<V>, double[], int, DiSHPreferenceVectorIndex.Strategy) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex: Constructor.
DiSHPreferenceVectorIndex.Factory<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Factory class.
DiSHPreferenceVectorIndex.Factory.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Parameterization class.
DiSHPreferenceVectorIndex.Strategy - Enum in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Available strategies for determination of the preference vector.
dishPreprocessor - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH: The DiSH preprocessor.
dishPreprocessor - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Parameterizer: DiSH preprocessor.
DisjointCrossValidation - Class in de.lmu.ifi.dbs.elki.evaluation.classification.holdout: DisjointCrossValidationHoldout provides a set of partitions of a database to perform cross-validation.
DisjointCrossValidation(RandomFactory, int) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation: Constructor.
DisjointCrossValidation.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.classification.holdout: Parameterization class
DiskCacheBasedDoubleDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Distance function that is based on double distances given by a distance matrix of an external binary matrix file.
DiskCacheBasedDoubleDistanceFunction(OnDiskUpperTriangleMatrix) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction: Constructor.
DiskCacheBasedDoubleDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Parameterization class.
DiskCacheBasedFloatDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Distance function that is based on float distances given by a distance matrix of an external binary matrix file.
DiskCacheBasedFloatDistanceFunction(OnDiskUpperTriangleMatrix) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction: Constructor.
DiskCacheBasedFloatDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Parameterization class.
DispatchingPanel(JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.DispatchingPanel: Constructor.
dispose() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.detail.DetailView
dispose() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow
dispose() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow
dispose() - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Clean up the plot.
dissimilarityMatrix() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult: Returns the dissimilarity matrix (M_czech) of this LocalPCA.
dist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch: Distribution to sample random replacement values from.
dist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: Distribution of replacement values.
dist - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster: Current height.
dist - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP: Type of distribution to assume for distances.
dist - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer: Distance distributution assumption.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter: Distribution to generate replacement values with.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.ReplaceNaNWithRandomFilter.Parameterizer: Distribution to generate replacement values with.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform: Distance function to use.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform.Parameterizer: Distance function to use.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.FastMultidimensionalScalingTransform: Distance function to use.
dist - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.FastMultidimensionalScalingTransform.Parameterizer: Distance function to use.
dist - Variable in class de.lmu.ifi.dbs.elki.index.vafile.PartialVAFile.WorstCaseDistComparator
dist - Variable in class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.COPOutlierScaling: Score distribution.
dist - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.index.TreeSphereVisualization.Instance: Drawing mode (distance) to use
DIST_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering.ChengAndChurch.Parameterizer: Parameter to specify the distribution of replacement values when masking a cluster.
DIST_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer: Distribution assumption for distances.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.DistanceBasedInitializationWithMedian: Distance function.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.DistanceBasedInitializationWithMedian.Parameterizer: istance function.
distance(ArrayDBIDs, int, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HDBSCANAdapter
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor: Distance function.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel.KMeansProcessor.Instance: Distance function.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair: The current distance.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU.Parameterizer
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering: Distance function for clusterings.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.RepresentativeUncertainClustering.Parameterizer: Distance (dissimilarity) for clusterinogs.
distance - Variable in class de.lmu.ifi.dbs.elki.algorithm.MaterializeDistances.DistanceEntry: Distance of the two objects
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix.Parameterizer: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceKNNLists: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceKNNLists.Parameterizer: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceRangeQueries: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceRangeQueries.Parameterizer: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheFloatDistanceInOnDiskMatrix: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.cache.CacheFloatDistanceInOnDiskMatrix.Parameterizer: Distance function that is to be cached.
distance - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment: Distance in use.
Distance() - Constructor for enum de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment.Distance
distance - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment.Parameterizer: Distance in use.
distance(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution: Returns the distance of NumberVector p from the hyperplane underlying this solution.
distance(Vector) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution: Returns the distance of Matrix p from the hyperplane underlying this solution.
distance - Variable in class de.lmu.ifi.dbs.elki.data.model.DendrogramModel: Distance to child cluster
distance(O, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDatabaseDistanceQuery
distance(DBIDRef, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDatabaseDistanceQuery
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDatabaseDistanceQuery
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(O, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(DBIDRef, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.AbstractDistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.DBIDDistanceQuery
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.DBIDRangeDistanceQuery
distance(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(O, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(DBIDRef, O) - Method in interface de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(O, O) - Method in interface de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery: Returns the distance between the two objects specified by their object ids.
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery
distance(O, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery
distance(DBIDRef, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDBIDRangeDistanceFunction
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter.Instance
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.ArcCosineDistanceFunction: Computes the cosine distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.BrayCurtisDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.CanberraDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.ClarkDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HistogramIntersectionDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsolutePearsonCorrelationDistanceFunction: Computes the absolute Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsoluteUncenteredCorrelationDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PearsonCorrelationDistanceFunction: Computes the Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredPearsonCorrelationDistanceFunction: Computes the squared Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredUncenteredCorrelationDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.UncenteredCorrelationDistanceFunction: Computes the Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedPearsonCorrelationDistanceFunction: Computes the Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedSquaredPearsonCorrelationDistanceFunction: Computes the squared Pearson correlation distance for two given feature vectors.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.CosineDistanceFunction: Computes the cosine distance for two given feature vectors.
distance(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.DBIDDistanceFunction: Returns the distance between the two objects specified by their object ids.
distance(int, int) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.DBIDRangeDistanceFunction: Compute the distance for two integer offsets.
distance(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction
distance(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction
distance(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedDoubleDistanceFunction
distance(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedFloatDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LatLngDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LngLatDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.HistogramMatchDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.KolmogorovSmirnovDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.Kulczynski1DistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.LorentzianDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.MatrixWeightedDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPIntegerNormDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPNormDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.ManhattanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MaximumDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MinimumDistanceFunction
distance(SparseNumberVector, SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseEuclideanDistanceFunction
distance(SparseNumberVector, SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseLPNormDistanceFunction
distance(SparseNumberVector, SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseManhattanDistanceFunction
distance(SparseNumberVector, SparseNumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseMaximumDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SquaredEuclideanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedEuclideanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedLPNormDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedManhattanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedMaximumDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedSquaredEuclideanDistanceFunction
distance(NumberVector, NumberVector) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.NumberVectorDistanceFunction: Computes the distance between two given vectors according to this distance function.
distance(O, O) - Method in interface de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction: Computes the distance between two given DatabaseObjects according to this distance function.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiSquaredDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.HellingerDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.JeffreyDivergenceDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.JensenShannonDivergenceDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceAsymmetricDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.SqrtJensenShannonDivergenceDistanceFunction
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.RandomStableDistanceFunction
distance(FeatureVector<?>, FeatureVector<?>) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.set.HammingDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.set.HammingDistanceFunction
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.set.JaccardSimilarityDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.set.JaccardSimilarityDistanceFunction
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.SharedNearestNeighborJaccardDistanceFunction.Instance
distance(String, String) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.strings.LevenshteinDistanceFunction
distance(String, String) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.strings.NormalizedLevenshteinDistanceFunction
distance(V, V) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction: Computes the distance between two given DatabaseObjects according to this distance function.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceEuclideanDistanceFunction: Constructor.
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceLPNormDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceManhattanDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceMaximumDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DerivativeDTWDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.LCSSDistanceFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.WeightedCanberraDistanceFunction
distance(Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringAdjustedRandIndexSimilarityFunction
distance(Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringBCubedF1SimilarityFunction
distance(Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringFowlkesMallowsSimilarityFunction
distance(Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusteringRandIndexSimilarityFunction
distance(Cluster<?>, Cluster<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusterIntersectionSimilarityFunction
distance(Cluster<?>, Cluster<?>) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.cluster.ClusterJaccardSimilarityFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.LinearKernelFunction
distance(NumberVector, NumberVector) - Method in class de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel.PolynomialKernelFunction
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette.Parameterizer: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer: Distance function to use.
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.PrecomputedDistanceQuery
distance(O, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.PrecomputedDistanceQuery
distance(DBIDRef, O) - Method in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.PrecomputedDistanceQuery
distance(O, O) - Method in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.PrecomputedDistanceQuery
distance - Variable in class de.lmu.ifi.dbs.elki.index.idistance.InMemoryIDistanceIndex.Factory: Distance function to use.
distance - Variable in class de.lmu.ifi.dbs.elki.index.idistance.InMemoryIDistanceIndex.Factory.Parameterizer: Distance function to use.
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Compute a distance (and count).
distance(O, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Compute a distance (and count).
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree: Returns the distance between the two specified ids.
distance(E, E) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree: Returns the distance between the routing object of two entries.
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree
distance(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex
distance - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.DistanceEntry: The distance value belonging to the entry.
distance - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery.DoubleDistanceEntry: Distance value
distance(DimensionSimilarityMatrix, int, int) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.PrimAdapter
distance(T, int, int) - Method in interface de.lmu.ifi.dbs.elki.math.geometry.PrimsMinimumSpanningTree.Adapter: Get the distance of two objects
distance(double[][], int, int) - Method in class de.lmu.ifi.dbs.elki.math.geometry.PrimsMinimumSpanningTree.Array2DAdapter
distance(NumberVector, NumberVector) - Method in class tutorial.distancefunction.MultiLPNorm
distance(NumberVector, NumberVector) - Method in class tutorial.distancefunction.TutorialDistanceFunction
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU: The distance function to determine the distance between database objects.
DISTANCE_FUNCTION_ID - Static variable in interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm: OptionID for DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.InvertedDistanceSimilarityFunction: Parameter to specify the similarity function to derive the distance between database objects from.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory: Parameter to indicate the distance function to be used to ascertain the nearest neighbors.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory: Parameter to indicate the distance function to be used to ascertain the nearest neighbors.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer: Parameter to specify the distance function to determine the distance between database objects, must extend DistanceFunction.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeFactory.Parameterizer: Parameter to specify the distance function to determine the distance between database objects, must extend DistanceFunction.
DISTANCE_FUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTreeFactory: Parameter for distance function
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.DistanceBasedInitializationWithMedian.Parameterizer: Parameter for the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceInOnDiskMatrix.Parameterizer: Parameter that specifies the name of the directory to be re-parsed.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceKNNLists.Parameterizer: Parameter that specifies the name of the directory to be re-parsed.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.cache.CacheDoubleDistanceRangeQueries.Parameterizer: Parameter that specifies the name of the directory to be re-parsed.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.GreedyEnsembleExperiment.Parameterizer: Similarity measure
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform.Parameterizer: Distant metric.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer: Parameter for choosing the distance function.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.Factory.Parameterizer: Option parameter for the precomputed distance matrix.
DISTANCE_ID - Static variable in class de.lmu.ifi.dbs.elki.index.idistance.InMemoryIDistanceIndex.Factory.Parameterizer: Parameter for the distance function
DistanceBasedAlgorithm<O> - Interface in de.lmu.ifi.dbs.elki.algorithm: Very broad interface for distance based algorithms.
DistanceBasedInitializationWithMedian<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Distance based initialization.
DistanceBasedInitializationWithMedian(DistanceFunction<? super O>, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.DistanceBasedInitializationWithMedian: Constructor.
DistanceBasedInitializationWithMedian.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation: Parameterization class.
DistanceCacheWriter - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction.external: Interface to plug in the cache storage into the parser.
distanceCalcs - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree.Statistics: For counting the number of distance computations.
distanceCalcs - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree.Statistics: For counting the number of distance computations.
DistanceCorrelationDependenceMeasure - Class in de.lmu.ifi.dbs.elki.math.statistics.dependence: Distance correlation.
DistanceCorrelationDependenceMeasure() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure: Constructor - use DistanceCorrelationDependenceMeasure.STATIC instance instead!
DistanceCorrelationDependenceMeasure.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.dependence: Parameterization class
distanceDeg(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
distanceDeg(double, double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel: Compute the geodetic distance between two surface coordinates.
DistanceDist() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.outlier.COP.DistanceDist
DistanceEntry(DBIDPair, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.MaterializeDistances.DistanceEntry: Constructor.
DistanceEntry<E extends Entry> - Class in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split: Helper class: encapsulates an entry in an Index and a distance value belonging to this entry.
DistanceEntry(E, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.DistanceEntry: Constructs a new DistanceEntry object with the specified parameters.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm: Holds the instance of the distance function specified by DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm.Parameterizer: The distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm: Holds the instance of the distance function specified by DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractNumberVectorDistanceBasedAlgorithm.Parameterizer: Distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractPrimitiveDistanceBasedAlgorithm: Holds the instance of the distance function specified by DistanceBasedAlgorithm.DISTANCE_FUNCTION_ID.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer: Distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedClustering: The Euclidean distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU: Holds the instance of the distance function specified by SUBCLU.DISTANCE_FUNCTION_ID.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI.Parameterizer: The distance function
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractDistanceBasedSpatialOutlier.Parameterizer: The distance function to use on the non-spatial attributes.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.database.query.distance.DBIDDistanceQuery: The distance function we use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.database.query.distance.DBIDRangeDistanceQuery: The distance function we use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.database.query.distance.PrimitiveDistanceQuery: The distance function we use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.database.query.distance.SpatialPrimitiveDistanceQuery: The distance function we use.
DistanceFunction<O> - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction: Base interface for any kind of distances.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.distance.similarityfunction.InvertedDistanceSimilarityFunction: Holds the similarity function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs: Distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin: Distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex: Distance function to use.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage: The distance function to use
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage.Parameterizer: The distance function to use
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix: Nested distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.Factory: Nested distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix.Factory.Parameterizer: Nested distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor: The distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory: Hold the distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor.Factory.Parameterizer: Hold the distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor: Hold the distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory: Hold the distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor.Factory.Parameterizer: Hold the distance function to be used.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Holds the instance of the trees distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory: Holds the instance of the trees distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer: Holds the instance of the trees distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeSettings: Holds the instance of the trees distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery: Spatial primitive distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeRangeQuery: Spatial primitive distance function
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdkNNSettings: The distance function.
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.AbstractPartialReinsert: Distance function to use for measuring
distanceFunction - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.reinsert.AbstractPartialReinsert.Parameterizer: Distance function to use for measuring
DISTANCEFUNCTION - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization.Instance
distanceFunction - Variable in class tutorial.clustering.SameSizeKMeansAlgorithm.Parameterizer: Distance function
DISTANCEFUNCTION_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer: Parameter to specify the distance function to use
DistanceFunctionVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection: Factory for visualizers to generate an SVG-Element containing dots as markers representing the kNN of the selected Database objects.
DistanceFunctionVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization: Constructor
DistanceFunctionVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection: Instance, visualizing a particular set of kNNs
DistanceIndex<O> - Interface in de.lmu.ifi.dbs.elki.index: Index with support for distance queries (e.g. precomputed distance matrixes, caches)
DistanceParser - Interface in de.lmu.ifi.dbs.elki.distance.distancefunction.external: A DistanceParser shall provide a DistanceParsingResult by parsing an InputStream.
DistanceQuery<O> - Interface in de.lmu.ifi.dbs.elki.database.query.distance: A distance query serves as adapter layer for database and primitive distances.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.database.query.knn.AbstractDistanceKNNQuery: Hold the distance function to be used.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.database.query.range.AbstractDistanceRangeQuery: Hold the distance function to be used.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.database.query.rknn.AbstractRKNNQuery: Hold the distance function to be used.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedDistanceMatrix: Nested distance query.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.idistance.InMemoryIDistanceIndex: Distance query.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor: The distance query we used.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Distance query, on the data relation.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.AbstractMkTree: Distance query to use.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree.MTreeIndex: The distance query.
distanceQuery - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree: The distance function.
distanceRad(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
distanceRad(double, double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel: Compute the geodetic distance between two surface coordinates.
distanceRad(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalCosineEarthModel
distanceRad(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalHaversineEarthModel
distanceRad(double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalVincentyEarthModel
DistanceResultAdapter - Class in de.lmu.ifi.dbs.elki.evaluation.scores.adapter: This adapter is used to process a list of (double, DBID) objects.
DistanceResultAdapter(DoubleDBIDListIter) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DistanceResultAdapter: Constructor
DistanceSimilarityQuery<O> - Interface in de.lmu.ifi.dbs.elki.database.query: Interface that is a combination of distance and a similarity function.
DistanceStatisticsWithClasses<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Algorithm to gather statistics over the distance distribution in the data set.
DistanceStatisticsWithClasses(DistanceFunction<? super O>, int, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses: Constructor.
DistanceStatisticsWithClasses.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Parameterization class.
DistanceStddevOutlier<O> - Class in tutorial.outlier: A simple outlier detection algorithm that computes the standard deviation of the kNN distances.
DistanceStddevOutlier(DistanceFunction<? super O>, int) - Constructor for class tutorial.outlier.DistanceStddevOutlier: Constructor.
DistanceStddevOutlier.Parameterizer<O> - Class in tutorial.outlier: Parameterization class
distcalc - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.MinimalisticMemoryKDTree: Counter for distance computations.
distcalc - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree: Counter for distance computations.
distComputations - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Distance computations performed.
distf - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores: Distance function to use
distf - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores.Parameterizer: Distance function to use
distfun - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer: Distance function to use
distfun - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Parameterizer: Distance function to use
distFunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate: Distance function to use.
distFunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate: Distance function to use
distfunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut.Parameterizer: LPNorm distance function
distFunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.ALOCI: Distance function
distFunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory: distance function to use
distFunc - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer: Distance function
distq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN.HDBSCANAdapter: Distance query for exact distances.
distq - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.HilOut: Distance query
distq - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery: Distance query to use for refinement
distq - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor.SpaceFillingKNNQuery: Distance query to use for refinement
distq - Variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.ProjectedKNNQuery: Distance query for refinement.
distq - Variable in class de.lmu.ifi.dbs.elki.index.projected.ProjectedIndex.ProjectedRKNNQuery: Distance query for refinement.
distribution - Variable in class de.lmu.ifi.dbs.elki.algorithm.classification.PriorProbabilityClassifier: Holds the prior probabilities.
Distribution - Interface in de.lmu.ifi.dbs.elki.math.statistics.distribution: Statistical distributions, with their common functions.
DistributionEstimator<D extends Distribution> - Interface in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator: Estimate distribution parameters from a sample.
DISTRIBUTIONS_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer: Parameter for distribution estimators.
DISTRIBUTIONS_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Parameterizer: Parameter for distribution estimators.
dists - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList: Distance values
dists - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization: Stores the estimated distributions
dists - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization: Stores the estimated distributions
dists - Variable in class tutorial.clustering.SameSizeKMeansAlgorithm.Meta: Distance to the cluster centers.
distToScale(double) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree: Convert a distance to an upper scaling bound-
DIV - Static variable in class de.lmu.ifi.dbs.elki.data.uncertain.SimpleGaussianContinuousUncertainObject: Scaling factor from bounding box width to standard deviations.
divide(DBIDArrayIter, double[], ArrayList<DBIDs>, int, int, int, Mean) - Method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.MCEDimensionSimilarity: Recursive call to further subdivide the array.
divide(int[], double[], ArrayList<int[]>, int, int, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.MCEDependenceMeasure: Recursive call to further subdivide the array.
dmax - Variable in class de.lmu.ifi.dbs.elki.visualization.projector.HistogramProjector: Database dimensionality.
dmax - Variable in class de.lmu.ifi.dbs.elki.visualization.projector.ScatterPlotProjector: Database dimensionality.
dnum - Variable in class de.lmu.ifi.dbs.elki.visualization.projections.Simple1D: Our dimension, starting with 0
doBulkReverseKNN(RdKNNNode, DBIDs, Map<DBID, ModifiableDoubleDBIDList>) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree: Performs a bulk reverse knn query in the specified subtree.
DOC<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: The DOC algorithm, and it's heuristic variant, FastDOC.
DOC(double, double, double, boolean, int, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC: Constructor.
DOC.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Parameterization class.
document - Variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: SVG document we plot to.
DOCUMENT_OPEN - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
DOCUMENT_PROPERTIES - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
DOCUMENT_SAVE - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
DocumentationUtil - Class in de.lmu.ifi.dbs.elki.utilities.documentation: Utilities for extracting documentation from class annotations.
DocumentationUtil() - Constructor for class de.lmu.ifi.dbs.elki.utilities.documentation.DocumentationUtil
DocumentParameters - Class in de.lmu.ifi.dbs.elki.application.internal: Class to generate HTML parameter descriptions for all classes that have ELKI Parameters.
DocumentParameters() - Constructor for class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters
DocumentParameters.SortByOption - Class in de.lmu.ifi.dbs.elki.application.internal: Sort parameters by their option
DocumentParameters.WikiStream - Class in de.lmu.ifi.dbs.elki.application.internal: Write to a Wiki format.
DocumentReferences - Class in de.lmu.ifi.dbs.elki.application.internal: Build a reference documentation for all available parameters.
DocumentReferences() - Constructor for class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
documentReferences(List<Pair<Reference, TreeSet<Object>>>) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
documentReferencesWiki(List<Pair<Reference, TreeSet<Object>>>, PrintStream) - Static method in class de.lmu.ifi.dbs.elki.application.internal.DocumentReferences
doDelete(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.HashmapDatabase: Removes the object with the specified id from this database.
doDetermineNextIntervalAtMaxLevel(ObjectHeap<IntegerPriorityObject<CASHInterval>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Recursive helper method to determine the next ''best'' interval at maximum level, i.e. the next interval containing the most unprocessed objects
doExtraIntegrityChecks() - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree: Perform additional integrity checks.
dof - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution: Degrees of freedom.
dof - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiDistribution.Parameterizer: Parameters.
dof - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution.Parameterizer: Parameters.
DOF_ID - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.ChiSquaredDistribution.Parameterizer: Degrees of freedom parameter.
dofit - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.LevenbergMarquardtMethod: Which parameters to fit
DOMCloner - Class in de.lmu.ifi.dbs.elki.utilities.xml: Class for cloning XML document, with filter capabilites
DOMCloner() - Constructor for class de.lmu.ifi.dbs.elki.utilities.xml.DOMCloner
DONT_CARE - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AbstractAggarwalYuOutlier: Symbolic value for subspaces not in use.
doRangeQuery(DBID, AbstractMTreeNode<O, ?, ?>, O, double, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query.MetricalIndexRangeQuery: Performs a range query on the specified subtree.
doReverseKNN(RdKNNNode, DBID, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNTree: Performs a reverse knn query in the specified subtree.
doReverseKNNQuery(int, DBIDRef, ModifiableDoubleDBIDList, ModifiableDBIDs) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPTree: Performs a reverse knn query.
doReverseKNNQuery(DBIDRef, MkMaxTreeNode<O>, MkMaxEntry, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxTree: Performs a reverse k-nearest neighbor query in the specified subtree for the given query object with k = AbstractMkTreeUnified.getKmax().
doReverseKNNQuery(int, DBIDRef, MkTabEntry, MkTabTreeNode<O>, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabTree: Performs a k-nearest neighbor query in the specified subtree for the given query object and the given parameter k.
doRun(Relation<ParameterizationFunction>, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH: Runs the CASH algorithm on the specified database, this method is recursively called until only noise is left.
doRunInTime(DBIDs, KNNQuery<O>, KNNQuery<O>, StepProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.FlexibleLOF: Performs the Generalized LOF_SCORE algorithm on the given database and returns a FlexibleLOF.LOFResult encapsulating information that may be needed by an OnlineLOF algorithm.
doSetParameters(List<String>) - Method in class de.lmu.ifi.dbs.elki.gui.minigui.MiniGUI: Do the actual setParameters invocation.
dotcolor - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.DashedLineStyleLibrary: Color of "uncolored" dots
dotcolor - Variable in class de.lmu.ifi.dbs.elki.visualization.style.lines.SolidLineStyleLibrary: Color of "uncolored" dots
dotcolor - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.CircleMarkers: Color of "uncolored" dots
dotcolor - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.MinimalMarkers: Color of "uncolored" dots
dotcolor - Variable in class de.lmu.ifi.dbs.elki.visualization.style.marker.PrettyMarkers: Color of "uncolored" dots
doThumbnail() - Method in interface de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs.ThumbnailThread.Listener: Callback when to (re-)compute the thumbnail.
doThumbnail() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs.ThumbnailVisualization
DOTMARKER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.MarkerVisualization.Instance: Generic tag to indicate the type of element.
DOTPLOT - Static variable in interface de.lmu.ifi.dbs.elki.visualization.style.StyleLibrary: Dot size
dotTableModel - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.SelectionTableWindow: The table model
DOUBLE - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Double type, outlier scores etc.
DOUBLE_ADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.QuickSelect: Adapter for double arrays.
DOUBLE_CACHE_MAGIC - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction: Magic to identify double cache matrices
DOUBLE_NULL - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.set.AbstractSetDistanceFunction: Constants for checking null.
DOUBLE_SERIALIZER - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil: Static instance.
DOUBLE_VECTOR_FIELD - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil: Input type for algorithms that require number vector fields.
DoubleArray - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Array of double values.
DoubleArray() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray: Constructor.
DoubleArray(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray: Constructor.
DoubleArray(DoubleArray) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArray: Constructor from an existing array.
DOUBLEARRAYADAPTER - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil: Use a double array in the array API.
doubleArrayAdapter() - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ArrayLikeUtil: Get the adapter for double arrays.
DoubleArrayAdapter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike: Use a double array as, well, double array in the ArrayAdapter API.
DoubleArrayAdapter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.DoubleArrayAdapter: Constructor.
DoubleArrayStaticHistogram - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Histogram containing an array of doubles (i.e.
DoubleArrayStaticHistogram(int, double, double, int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleArrayStaticHistogram: Constructor.
doubleCenterMatrix(double[], int) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure: Computes the distance variance matrix of one axis.
doubleCenterSymmetric(double[][]) - Static method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.ClassicMultidimensionalScalingTransform: Double-center the given matrix (only upper triangle is used).
DoubleDataStore - Interface in de.lmu.ifi.dbs.elki.database.datastore: Double-valued data store (avoids boxing/unboxing).
DoubleDBIDList - Interface in de.lmu.ifi.dbs.elki.database.ids: Collection of double values associated with objects.
DoubleDBIDListIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Iterator over double-DBID pairs results.
DoubleDBIDListMIter - Interface in de.lmu.ifi.dbs.elki.database.ids: Modifiable DBIDList iterator.
DoubleDBIDPair - Interface in de.lmu.ifi.dbs.elki.database.ids: Pair of a double value and a DBID.
DoubleDistanceEntry(SpatialEntry, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery.DoubleDistanceEntry: Constructor.
DoubleDistanceSearchCandidate - Class in de.lmu.ifi.dbs.elki.index.tree.query: Candidate for expansion in a distance search (double optimized implementation).
DoubleDistanceSearchCandidate(double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.query.DoubleDistanceSearchCandidate: Constructor.
DoubleDoublePair - Class in de.lmu.ifi.dbs.elki.utilities.pairs: Pair storing two doubles.
DoubleDoublePair(double, double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair: Constructor
DoubleDoublePair(DoubleDoublePair) - Constructor for class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair: Clone constructor.
DoubleDynamicHistogram - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: A flexible histogram storing double, that can dynamically adapt the number of bins to the data fed into the histogram.
DoubleDynamicHistogram(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram: Constructor.
DoubleHeap - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Basic in-memory heap for double values.
DoubleHeap.UnsortedIter - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleHistogram - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Histogram storing double values.
DoubleHistogram.Iter - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Iterator interface.
DoubleIntArrayList(int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI.DoubleIntArrayList: Constructor.
DoubleIntegerArrayQuickSort - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arrays: Class to sort a double and an integer DBID array, using a quicksort with a best of 5 heuristic.
DoubleIntegerArrayQuickSort() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arrays.DoubleIntegerArrayQuickSort
DoubleIntegerDBIDKNNHeap - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Class to efficiently manage a kNN heap.
DoubleIntegerDBIDKNNHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNHeap: Constructor.
DoubleIntegerDBIDKNNList - Class in de.lmu.ifi.dbs.elki.database.ids.integer: kNN list, but without automatic sorting.
DoubleIntegerDBIDKNNList() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNList: Constructor.
DoubleIntegerDBIDKNNList(int, int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDKNNList: Constructor.
DoubleIntegerDBIDList - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Class to store double distance, integer DBID results.
DoubleIntegerDBIDList() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList: Constructor.
DoubleIntegerDBIDList(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList: Constructor.
DoubleIntegerDBIDList.Itr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: List iterator.
DoubleIntegerDBIDListIter - Interface in de.lmu.ifi.dbs.elki.database.ids.integer: Combination interface of the DoubleDBIDListIter with IntegerDBIDIter.
DoubleIntegerDBIDListKNNHeap - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Track the k nearest neighbors, with insertion sort to ensure the correct order.
DoubleIntegerDBIDListKNNHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDListKNNHeap: Constructor.
DoubleIntegerDBIDListMIter - Interface in de.lmu.ifi.dbs.elki.database.ids.integer: Combination interface for modifiable iterators.
DoubleIntegerDBIDPair - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Pair containing a double value and an integer DBID.
DoubleIntegerDBIDPair(double, int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPair: Constructor.
DoubleIntegerDBIDPairKNNListHeap - Class in de.lmu.ifi.dbs.elki.database.ids.integer: KNN Heap implemented using a list of DoubleInt pair objects.
DoubleIntegerDBIDPairKNNListHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap: Constructor.
DoubleIntegerDBIDPairKNNListHeap.Itr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Iterator.
DoubleIntegerDBIDPairList - Class in de.lmu.ifi.dbs.elki.database.ids.integer: Class to store double distance, integer DBID results.
DoubleIntegerDBIDPairList() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList: Constructor.
DoubleIntegerDBIDPairList(int) - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList: Constructor.
DoubleIntegerDBIDPairList.Itr - Class in de.lmu.ifi.dbs.elki.database.ids.integer: List iterator.
DoubleIntegerHeap - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Basic in-memory heap interface, for double keys and int values.
DoubleIntegerHeap.UnsortedIter - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleIntegerMaxHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleIntegerMaxHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap: Constructor, with default size.
DoubleIntegerMaxHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap: Constructor, with given minimum size.
DoubleIntegerMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleIntegerMinHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleIntegerMinHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap: Constructor, with default size.
DoubleIntegerMinHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap: Constructor, with given minimum size.
DoubleIntegerMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleIntInt(double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS.DoubleIntInt
DoubleIntPair - Class in de.lmu.ifi.dbs.elki.utilities.pairs: Pair storing an integer and a double.
DoubleIntPair(double, int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleIntPair: Constructor
DoubleListParameter - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters: Parameter class for a parameter specifying a list of double values.
DoubleListParameter(OptionID, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleListParameter: Constructs a list parameter with the given optionID and optional flag.
DoubleListParameter(OptionID) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleListParameter: Constructs a list parameter with the given optionID.
DoubleLongHeap - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Basic in-memory heap interface, for double keys and long values.
DoubleLongHeap.UnsortedIter - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleLongMaxHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleLongMaxHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap: Constructor, with default size.
DoubleLongMaxHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap: Constructor, with given minimum size.
DoubleLongMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleLongMinHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleLongMinHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap: Constructor, with default size.
DoubleLongMinHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap: Constructor, with given minimum size.
DoubleLongMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleMaxHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleMaxHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap: Constructor, with default size.
DoubleMaxHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap: Constructor, with given minimum size.
DoubleMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleMinHeap - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleMinHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap: Constructor, with default size.
DoubleMinHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap: Constructor, with given minimum size.
DoubleMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleMinMax - Class in de.lmu.ifi.dbs.elki.math: Class to find the minimum and maximum double values in data.
DoubleMinMax() - Constructor for class de.lmu.ifi.dbs.elki.math.DoubleMinMax: Constructor without starting values.
DoubleMinMax(double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.DoubleMinMax: Constructor with predefined minimum and maximum values.
DoubleMinMaxProcessor - Class in de.lmu.ifi.dbs.elki.parallel.processor: Sink collecting minimum and maximum values.
DoubleMinMaxProcessor() - Constructor for class de.lmu.ifi.dbs.elki.parallel.processor.DoubleMinMaxProcessor: Constructor.
DoubleMinMaxProcessor.Instance - Class in de.lmu.ifi.dbs.elki.parallel.processor: Instance for a particular sub-channel / part of the data set.
DoubleMTreeDistanceSearchCandidate - Class in de.lmu.ifi.dbs.elki.index.tree.query: Encapsulates the attributes for a object that can be stored in a heap.
DoubleMTreeDistanceSearchCandidate(double, int, DBID, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.query.DoubleMTreeDistanceSearchCandidate: Creates a new heap node with the specified parameters.
DoubleObjectHeap<V> - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Basic in-memory heap interface, for double keys and V values.
DoubleObjectHeap.UnsortedIter<V> - Interface in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleObjectMaxHeap<V> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleObjectMaxHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap: Constructor, with default size.
DoubleObjectMaxHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap: Constructor, with given minimum size.
DoubleObjectMaxHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleObjectMinHeap<V> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Binary heap for primitive types.
DoubleObjectMinHeap() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap: Constructor, with default size.
DoubleObjectMinHeap(int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap: Constructor, with given minimum size.
DoubleObjectMinHeap.UnsortedIter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Unsorted iterator - in heap order.
DoubleObjPair<O> - Class in de.lmu.ifi.dbs.elki.utilities.pairs: Pair storing a native double value and an arbitrary object.
DoubleObjPair(double, O) - Constructor for class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleObjPair: Constructor.
DoubleParameter - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters: Parameter class for a parameter specifying a double value.
DoubleParameter(OptionID, double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter: Constructs a double parameter with the given optionID and default value.
DoubleParameter(OptionID) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter: Constructs a double parameter with the given optionID.
DoublePriorityObject<O> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.heap: Object for a priority queue with integer priority.
DoublePriorityObject(double, O) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoublePriorityObject: Constructor.
DoubleRelation - Interface in de.lmu.ifi.dbs.elki.database.relation: Interface for double-valued relations.
DoubleSerializer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil.DoubleSerializer: Constructor.
DoubleStaticHistogram - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Histogram class storing double values.
DoubleStaticHistogram(int, double, double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleStaticHistogram: Constructor.
DoubleStaticHistogram.Iter - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.histogram: Iterator class.
DoubleStatistic - Class in de.lmu.ifi.dbs.elki.logging.statistics: Trivial double-valued statistic.
DoubleStatistic(String) - Constructor for class de.lmu.ifi.dbs.elki.logging.statistics.DoubleStatistic: Constructor.
DoubleStatistic(String, double) - Constructor for class de.lmu.ifi.dbs.elki.logging.statistics.DoubleStatistic: Constructor.
doubleValue() - Method in class de.lmu.ifi.dbs.elki.data.Bit
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.BitVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.ByteVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.DoubleVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.FloatVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.IntegerVector
doubleValue(int) - Method in interface de.lmu.ifi.dbs.elki.data.NumberVector: Returns the value in the specified dimension as double.
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.OneDimensionalDoubleVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.ShortVector
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.SparseByteVector: Deprecated.
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.SparseDoubleVector: Deprecated.
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.SparseFloatVector: Deprecated.
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.SparseIntegerVector: Deprecated.
doubleValue(int) - Method in interface de.lmu.ifi.dbs.elki.data.SparseNumberVector: Deprecated.
As the vectors are sparse, try to iterate over the sparse dimensions only, see SparseNumberVector.iterDoubleValue(int).
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.data.SparseShortVector: Deprecated.
doubleValue(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.datastore.DoubleDataStore: Retrieves an object from the storage.
doubleValue(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayDoubleStore
doubleValue(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.datastore.memory.MapIntegerDBIDDoubleStore
doubleValue() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDListIter: Get the double value
doubleValue() - Method in interface de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair: Get the double value of the pair.
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.KNNSubList.Itr
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList.Itr
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPair
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap.Itr
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList.Itr
doubleValue() - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDKNNSubList.Itr
doubleValue(DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.relation.DoubleRelation: Get the representation of an object.
doubleValue(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.relation.MaterializedDoubleRelation
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.SpatialPointLeafEntry
doubleValue(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
doubleValue() - Method in class de.lmu.ifi.dbs.elki.parallel.variables.SharedDouble.Instance: Get the variables value.
doubleValue() - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter: Get the parameter value as double.
DoubleVector - Class in de.lmu.ifi.dbs.elki.data: Vector type using double[] storage for real numbers.
DoubleVector(double[], boolean) - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector: Private constructor.
DoubleVector(double[]) - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector: Create a DoubleVector consisting of the given double values.
DoubleVector(Vector) - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector: Expects a matrix of one column.
DoubleVector.Factory - Class in de.lmu.ifi.dbs.elki.data: Factory for Double vectors.
DoubleVector.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.data: Parameterization class.
DoubleVector.ShortSerializer - Class in de.lmu.ifi.dbs.elki.data: Serialization class for dense double vectors with up to Short.MAX_VALUE dimensions, by using a short for storing the dimensionality.
DoubleVector.SmallSerializer - Class in de.lmu.ifi.dbs.elki.data: Serialization class for dense double vectors with up to 127 dimensions, by using a byte for storing the dimensionality.
DoubleVector.VariableSerializer - Class in de.lmu.ifi.dbs.elki.data: Serialization class for variable dimensionality by using VarInt encoding.
DOWN - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGArrow: Constant for "down"
downsample(Object[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.AbstractObjDynamicHistogram: Perform downsampling on a number of bins.
downsample(double[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleDynamicHistogram: Perform downsampling on a number of bins.
downsample(float[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.FloatDynamicHistogram: Perform downsampling on a number of bins.
downsample(int[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.IntDynamicHistogram: Perform downsampling on a number of bins.
downsample(long[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.LongDynamicHistogram: Perform downsampling on a number of bins.
downsample(short[], int, int, int) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.ShortDynamicHistogram: Perform downsampling on a number of bins.
DragableArea - Class in de.lmu.ifi.dbs.elki.visualization.batikutil: A simple dragable area for Batik.
DragableArea(SVGPlot, double, double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Constructor for a dragable area. use getElement() to get the DOM node.
DragableArea(SVGPlot, Element, double, double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Constructor for a dragable area. use getElement() to get the DOM node.
DragableArea(SVGPlot, double, double, double, double, DragableArea.DragListener) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Constructor for a dragable area. use getElement() to get the DOM node.
DragableArea(SVGPlot, Element, double, double, double, double, DragableArea.DragListener) - Constructor for class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Constructor for a dragable area. use getElement() to get the DOM node.
DragableArea.DragListener - Interface in de.lmu.ifi.dbs.elki.visualization.batikutil: Listener interface for drag events.
drawArc(SVGPath, Vector, Vector, Vector, Vector, Vector, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Draw an arc to simulate the hyper ellipse.
drawAxis(SVGPlot, Element, LinearScale, double, double, double, double, SVGSimpleLinearAxis.LabelStyle, StyleLibrary) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGSimpleLinearAxis: Plot an axis with appropriate scales
drawClusteringInfo() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance
drawClusters(Clustering<OPTICSModel>, Hierarchy.Iter<Cluster<OPTICSModel>>, int, Map<Cluster<?>, String>) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSClusterVisualization.Instance: Recursively draw clusters
drawContinuous(UncertainObject, MarkerLibrary, int, double, Random) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization.Instance: Visualize random samples
drawContinuousDefault(UncertainObject, int, double, Random) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization.Instance: Visualize random samples
drawCosine(SVGPlot, Projection2D, NumberVector, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization: Visualizes Cosine and ArcCosine distance functions
drawCross(SVGPlot, Projection2D, NumberVector, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere: Wireframe "cross" hypersphere
drawDelaunay(Projection2D, List<SweepHullDelaunay2D.Triangle>, List<double[]>) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.VoronoiDraw: Draw the Delaunay triangulation.
drawDiscete(DiscreteUncertainObject, MarkerLibrary, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization.Instance: Visualize a discrete uncertain object
drawDiscreteDefault(DiscreteUncertainObject, int, double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.uncertain.UncertainSamplesVisualization.Instance: Visualize discrete object
drawEuclidean(SVGPlot, Projection2D, NumberVector, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere: Wireframe "euclidean" hypersphere
drawFakeVoronoi(Projection2D, List<double[]>) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.VoronoiDraw: Fake Voronoi diagram.
drawFilled(SVGPlot, String, Projection2D, double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Filled hypercube.
drawFilled(SVGPlot, String, Projection2D, NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Filled hypercube.
drawFilled(SVGPlot, String, Projection2D, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Filled hypercube.
drawFrame(SVGPlot, Projection2D, double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Wireframe hypercube.
drawFrame(SVGPlot, Projection2D, NumberVector, NumberVector) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Wireframe hypercube.
drawFrame(SVGPlot, Projection2D, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperCube: Wireframe hypercube.
drawHierarchy(SVGPlot, MarkerLibrary, DoubleDoublePair, DoubleDoublePair, int, Cluster<Model>, TObjectIntMap<Cluster<Model>>, Hierarchy<Cluster<Model>>) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.KeyVisualization.Instance
drawHullArc(String, Vector, Polygon) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Approximate the hull using arcs.
drawHullLines(String, Vector, Polygon) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Approximate by convex hull.
drawLine(int, int, int, int, boolean[][]) - Static method in class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HSMDimensionSimilarity: Draw a line onto the array, using the classic Bresenham algorithm.
drawLine(int, int, int, int, boolean[][]) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.dependence.HSMDependenceMeasure: Draw a line onto the array, using the classic Bresenham algorithm.
drawLine(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.BoundingBoxVisualization.Instance: Draw a single line.
drawLine(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.LineVisualization.Instance: Draw a single line.
drawLine(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionLineVisualization.Instance: Draw a single line.
drawLp(SVGPlot, Projection2D, NumberVector, double, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere: Wireframe "Lp" hypersphere
drawManhattan(SVGPlot, Projection2D, NumberVector, double) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere: Wireframe "manhattan" hypersphere
drawSample(Random) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.AbstractUncertainObject
drawSample(Random) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.SimpleGaussianContinuousUncertainObject
drawSample(Random) - Method in interface de.lmu.ifi.dbs.elki.data.uncertain.UncertainObject: Draw a random sampled instance.
drawSample(Random) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.UniformContinuousUncertainObject
drawSample(Random) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.UnweightedDiscreteUncertainObject
drawSample(Random) - Method in class de.lmu.ifi.dbs.elki.data.uncertain.WeightedDiscreteUncertainObject
drawSegments() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance: Create the segments
drawSphere2D(String, Vector, Vector[]) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance: Draw by approximating a sphere via cubic splines
drawStyle - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance
drawTo(double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath: Draw a line given a series of coordinates.
drawTo(double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath: Draw a line given a series of coordinates.
drawTo(Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath: Draw a line given a series of coordinates.
drawVoronoi(Projection2D, List<SweepHullDelaunay2D.Triangle>, List<double[]>) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.VoronoiDraw: Draw a Voronoi diagram
dropdownEditor - Variable in class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.AdjustingEditor: The dropdown editor
DropdownEditor(JComboBox<String>) - Constructor for class de.lmu.ifi.dbs.elki.gui.util.ParameterTable.DropdownEditor: Constructor.
DropEigenPairFilter - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca: The "drop" filter looks for the largest drop in normalized relative eigenvalues.
DropEigenPairFilter(double) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.DropEigenPairFilter: Constructor.
DropEigenPairFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca: Parameterization class.
dropfirst - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization.FarthestPointsInitialMeans: Discard the first vector.
DropNaNFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.cleaning: A filter to drop all records that contain NaN values.
DropNaNFilter() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.DropNaNFilter: Constructor.
DropNaNFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.cleaning: Parameterization class.
DTWDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Dynamic Time Warping distance (DTW) for numerical vectors.
DTWDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction: Constructor.
DTWDistanceFunction(double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction: Constructor.
DTWDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Parameterization class.
DummyAlgorithm<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm: Dummy algorithm, which just iterates over all points once, doing a 10NN query each.
DummyAlgorithm() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.DummyAlgorithm: Constructor.
dumpClusteringOutput(PrintStream, ResultHierarchy, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.result.ClusteringVectorDumper: Dump a single clustering result.
dumpDebugFile() - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot: Dump the SVG plot to a debug file.
Duration - Interface in de.lmu.ifi.dbs.elki.logging.statistics: Class that tracks the duration of a task.
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in interface de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea.DragListener: Method called during drags.
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea: Method called during drags.
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance
duringDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance
DWOF<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier: Algorithm to compute dynamic-window outlier factors in a database based on a specified parameter DWOF.Parameterizer.K_ID (-dwof.k).
DWOF(DistanceFunction<? super O>, int, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF: Constructor.
DWOF.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier: Parameterization class.
DYNAMIC_SERIALIZER - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID: The public instance to use for dynamic serialization.
dynamicids - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.SimpleDBIDFactory: Keep track of the smallest dynamic DBID offset not used.
DynamicIndex - Interface in de.lmu.ifi.dbs.elki.index: Index that supports dynamic insertions and removals.
DynamicMenu() - Constructor for class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu: Constructor.
DynamicParameters - Class in de.lmu.ifi.dbs.elki.gui.util: Wrapper around a set of parameters for ELKI, that may not yet be complete or correct.
DynamicParameters() - Constructor for class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters: Constructor
DynamicParameters.Node - Class in de.lmu.ifi.dbs.elki.gui.util: Node in the option tree (well, actually list)
DynamicParameters.RemainingOptions - Class in de.lmu.ifi.dbs.elki.gui.util: Dummy option class that represents unhandled options
DynamicSerializer() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID.DynamicSerializer: Constructor.
dynamicStart - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ReusingDBIDFactory: Keep track of the lowest unused dynamic DBID
dynamicUsed - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ReusingDBIDFactory: Bit set to keep track of dynamic DBIDs

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