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.arraylike.IntegerArray: (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.
DatabaseEventManager.Type() - Constructor for enum de.lmu.ifi.dbs.elki.database.DatabaseEventManager.Type
DatabaseQuery - Interface in de.lmu.ifi.dbs.elki.database.query: General interface for database queries.
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.AscendingByDoubleDataStore(DoubleDataStore) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.AscendingByDoubleDataStore: Constructor.
DataStoreUtil.AscendingByDoubleDataStoreAndId - Class in de.lmu.ifi.dbs.elki.database.datastore: Sort objects by a double relation
DataStoreUtil.AscendingByDoubleDataStoreAndId(DoubleDataStore) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.AscendingByDoubleDataStoreAndId: Constructor.
DataStoreUtil.DescendingByDoubleDataStore - Class in de.lmu.ifi.dbs.elki.database.datastore: Sort objects by a double relation
DataStoreUtil.DescendingByDoubleDataStore(DoubleDataStore) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByDoubleDataStore: Constructor.
DataStoreUtil.DescendingByDoubleDataStoreAndId - Class in de.lmu.ifi.dbs.elki.database.datastore: Sort objects by a double relation
DataStoreUtil.DescendingByDoubleDataStoreAndId(DoubleDataStore) - Constructor for class de.lmu.ifi.dbs.elki.database.datastore.DataStoreUtil.DescendingByDoubleDataStoreAndId: Constructor.
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.
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.
DBIDRangeDatabaseConnection.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.DBIDRangeDatabaseConnection.Parameterizer
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 (but not single DBIDs).
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<? super 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.
DBOutlierDetection.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierDetection.Parameterizer
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<? super 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.
DBOutlierScore.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.DBOutlierScore.Parameterizer
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.
DBSCAN.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.Parameterizer
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.
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.intrinsic - package de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic: Outlier detection algorithms based on intrinsic dimensionality.
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.
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.extractor - package de.lmu.ifi.dbs.elki.evaluation.clustering.extractor: Classes to extract clusterings from hierarchical clustering.
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.datastructures.unionfind - package de.lmu.ifi.dbs.elki.utilities.datastructures.unionfind
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.
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(double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.AbstractSimpleProjection: Undo the rearrangement of components.
dearrange(double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.projections.Simple1D
dearrange(double[]) - 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.
def - Variable in class de.lmu.ifi.dbs.elki.database.datastore.memory.ArrayIntegerStore: Default value (for ArrayIntegerStore.clear()).
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_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_SAMPLE_SIZE - Static variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer: Default sample size to visualize.
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.result.AutomaticVisualization: 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.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.Parameterizer
DeLiClu.SpatialObjectPair - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.optics: Encapsulates an entry in the cluster order.
DeLiClu.SpatialObjectPair(double, SpatialEntry, SpatialEntry, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair: Creates a new entry with the specified parameters.
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.
DeLiCluTreeFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTreeFactory.Parameterizer
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.
DendrogramVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Dendrogram visualizer.
DendrogramVisualization(DendrogramVisualization.Style) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization: Constructor.
DendrogramVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Visualization instance.
DendrogramVisualization.Instance(VisualizationTask, VisualizationPlot, double, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.Instance: Constructor.
DendrogramVisualization.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Parameterization class.
DendrogramVisualization.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.Parameterizer
DendrogramVisualization.Style - Enum in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Styles for dendrograms.
DendrogramVisualization.Style() - Constructor for enum de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.Style
DendrogramVisualization.SwitchStyleAction - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj: Menu item to change visualization styles.
DendrogramVisualization.SwitchStyleAction(VisualizationTask, VisualizerContext) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.DendrogramVisualization.SwitchStyleAction: 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.
DensityEstimationOverlay.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.density.DensityEstimationOverlay.Instance: Constructor.
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.
DependencyDerivator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.DependencyDerivator.Parameterizer
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.
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
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.
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
DiagonalGaussianModelFactory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModelFactory.Parameterizer
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.GriDBSCAN.Instance: Dimensionality.
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.filter.typeconversions.WeightedUncertainSplitFilter.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.
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.
DimensionSelectingLatLngDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction.Parameterizer
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.FullDimensionSimilarityMatrix(int) - Constructor for class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.FullDimensionSimilarityMatrix: Constructor.
DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Partial matrix of pairwise dimension similarities.
DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix(int[]) - Constructor for class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.PartialDimensionSimilarityMatrix: Constructor.
DimensionSimilarityMatrix.PrimAdapter - Class in de.lmu.ifi.dbs.elki.math.dimensionsimilarity: Adapter class for running prim's algorithm.
DimensionSimilarityMatrix.PrimAdapter() - Constructor for class de.lmu.ifi.dbs.elki.math.dimensionsimilarity.DimensionSimilarityMatrix.PrimAdapter: Constructor.
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.datasource.filter.typeconversions.WeightedUncertainSplitFilter: Data dimensionality.
dims - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.WeightedUncertainSplitFilter.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).
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_ID - Static variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.ComputeKNNOutlierScores.Parameterizer: Option ID for disabling 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.
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.DiSHClusterOrder(String, String, ArrayModifiableDBIDs, WritableDoubleDataStore, WritableDBIDDataStore, WritableIntegerDataStore, WritableDataStore<long[]>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.DiSHClusterOrder: Constructor.
DiSH.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: OPTICS variant used by DiSH internally.
DiSH.Instance(Database, Relation<V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance: Constructor.
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.Instance.Sorter() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance.Sorter
DiSH.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace: Parameterization class.
DiSH.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Parameterizer
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(double[], int, DiSHPreferenceVectorIndex.Strategy) - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory: Constructor.
DiSHPreferenceVectorIndex.Factory.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Parameterization class.
DiSHPreferenceVectorIndex.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory.Parameterizer
DiSHPreferenceVectorIndex.Strategy - Enum in de.lmu.ifi.dbs.elki.index.preprocessed.preference: Available strategies for determination of the preference vector.
DiSHPreferenceVectorIndex.Strategy() - Constructor for enum de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Strategy
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
DisjointCrossValidation.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.classification.holdout.DisjointCrossValidation.Parameterizer
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(File) - 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.
DiskCacheBasedDoubleDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction.Parameterizer
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(File) - 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.
DiskCacheBasedFloatDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction.Parameterizer
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 - 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_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.
DistanceBasedInitializationWithMedian.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation.DistanceBasedInitializationWithMedian.Parameterizer
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.
distanceComputations - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics.RandomProjectedNeighborsAndDensities: Count 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
DistanceCorrelationDependenceMeasure.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.dependence.DistanceCorrelationDependenceMeasure.Parameterizer
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.
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.GriDBSCAN.Instance: Distance function used.
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_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
DistanceFunctionVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.DistanceFunctionVisualization.Instance: Constructor
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.
DistanceQuantileSampler<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Compute a quantile of a distance sample, useful for choosing parameters for algorithms.
DistanceQuantileSampler(DistanceFunction<? super O>, double, double, boolean, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceQuantileSampler: Constructor.
DistanceQuantileSampler.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Parameterization class
DistanceQuantileSampler.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceQuantileSampler.Parameterizer
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.
DistanceStatisticsWithClasses.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer
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
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.
DOC.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DOC.Parameterizer
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.SortByOption() - Constructor for class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters.SortByOption
DocumentParameters.WikiStream - Class in de.lmu.ifi.dbs.elki.application.internal: Write to a Wiki format.
DocumentParameters.WikiStream(PrintStream) - Constructor for class de.lmu.ifi.dbs.elki.application.internal.DocumentParameters.WikiStream
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
domain - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance: Value domain.
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.
DoubleArrayListParameter - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters: Parameter class for a parameter specifying a list of vectors.
DoubleArrayListParameter(OptionID, ParameterConstraint<List<double[]>>, List<double[]>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
DoubleArrayListParameter(OptionID, ParameterConstraint<List<double[]>>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
DoubleArrayListParameter(OptionID, ParameterConstraint<List<double[]>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
DoubleArrayListParameter(OptionID, List<double[]>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
DoubleArrayListParameter(OptionID, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
DoubleArrayListParameter(OptionID) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleArrayListParameter: Constructs a vector list parameter with the given name and description.
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.
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.
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.
DoubleIntegerDBIDList.Itr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList.Itr: Constructor.
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.
DoubleIntegerDBIDPairKNNListHeap.Itr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairKNNListHeap.Itr
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.
DoubleIntegerDBIDPairList.Itr() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDPairList.Itr
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.
DoubleIntegerMaxHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMaxHeap.UnsortedIter
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.
DoubleIntegerMinHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleIntegerMinHeap.UnsortedIter
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.
DoubleLongMaxHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMaxHeap.UnsortedIter
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.
DoubleLongMinHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleLongMinHeap.UnsortedIter
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.
DoubleMaxHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMaxHeap.UnsortedIter
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.
DoubleMinHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleMinHeap.UnsortedIter
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.
DoubleMinMaxProcessor.Instance(SharedDouble.Instance) - Constructor for class de.lmu.ifi.dbs.elki.parallel.processor.DoubleMinMaxProcessor.Instance: Constructor.
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.
DoubleObjectMaxHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMaxHeap.UnsortedIter
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.
DoubleObjectMinHeap.UnsortedIter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoubleObjectMinHeap.UnsortedIter
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.
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.
DoubleStaticHistogram.Iter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.histogram.DoubleStaticHistogram.Iter
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() - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector.Factory
DoubleVector.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.data: Parameterization class.
DoubleVector.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector.Factory.Parameterizer
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.ShortSerializer() - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector.ShortSerializer
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.SmallSerializer() - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector.SmallSerializer
DoubleVector.VariableSerializer - Class in de.lmu.ifi.dbs.elki.data: Serialization class for variable dimensionality by using VarInt encoding.
DoubleVector.VariableSerializer() - Constructor for class de.lmu.ifi.dbs.elki.data.DoubleVector.VariableSerializer
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
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.
DropEigenPairFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.DropEigenPairFilter.Parameterizer
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.
DropNaNFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.cleaning.DropNaNFilter.Parameterizer
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.
DTWDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction.Parameterizer
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.
DWOF.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.DWOF.Parameterizer
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.
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.Node(Parameter<?>, String, int, int) - Constructor for class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters.Node: Constructor.
DynamicParameters.RemainingOptions - Class in de.lmu.ifi.dbs.elki.gui.util: Dummy option class that represents unhandled options
DynamicParameters.RemainingOptions() - Constructor for class de.lmu.ifi.dbs.elki.gui.util.DynamicParameters.RemainingOptions: 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

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