Uses of Interface
de.lmu.ifi.dbs.elki.database.Database

Packages that use Database

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.benchmark	Benchmarking pseudo algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan	Generalized DBSCAN.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.clustering.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.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods.
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	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application.cache	Utility applications for the persistence layer such as distance cache builders.
de.lmu.ifi.dbs.elki.application.greedyensemble	Greedy ensembles for outlier detection.
de.lmu.ifi.dbs.elki.application.jsmap	JavaScript based map client - server architecture.
de.lmu.ifi.dbs.elki.application.visualization	Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.relation	Relations, materialized and virtual (views).
de.lmu.ifi.dbs.elki.evaluation.histogram	Functionality for the evaluation of algorithms using histograms.
de.lmu.ifi.dbs.elki.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.optics	Result classes for OPTICS.
de.lmu.ifi.dbs.elki.result.textwriter	Text serialization (CSV, Gnuplot, Console, ...)
de.lmu.ifi.dbs.elki.utilities	Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.visualization	Visualization package of ELKI.
de.lmu.ifi.dbs.elki.visualization.gui	Package to provide a visualization GUI.
de.lmu.ifi.dbs.elki.workflow	Work flow packages, e.g. following the usual KDD model, closely related to CRISP-DM
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.
tutorial.outlier

Uses of Database in de.lmu.ifi.dbs.elki.algorithm

Methods in de.lmu.ifi.dbs.elki.algorithm with parameters of type Database

Modifier and Type	Method and Description
Result	NullAlgorithm.run(Database database)
R	AbstractAlgorithm.run(Database database)
Result	Algorithm.run(Database database) Runs the algorithm.
AprioriResult	APRIORI.run(Database database, Relation<BitVector> relation) Performs the APRIORI algorithm on the given database.
Result	DummyAlgorithm.run(Database database, Relation<O> relation) Run the algorithm.
KNNDistanceOrderResult<D>	KNNDistanceOrder.run(Database database, Relation<O> relation) Provides an order of the kNN-distances for all objects within the specified database.
CollectionResult<CTriple<DBID,DBID,Double>>	MaterializeDistances.run(Database database, Relation<O> relation) Iterates over all points in the database.
WritableDataStore<KNNResult<D>>	KNNJoin.run(Database database, Relation<V> relation) Joins in the given spatial database to each object its k-nearest neighbors.
CorrelationAnalysisSolution<V>	DependencyDerivator.run(Database database, Relation<V> relation) Computes quantitatively linear dependencies among the attributes of the given database based on a linear correlation PCA.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.benchmark

Methods in de.lmu.ifi.dbs.elki.algorithm.benchmark with parameters of type Database

Modifier and Type	Method and Description
Result	RangeQueryBenchmarkAlgorithm.run(Database database, Relation<O> relation) Run the algorithm, with a separate query set.
Result	KNNBenchmarkAlgorithm.run(Database database, Relation<O> relation) Run the algorithm.
Result	RangeQueryBenchmarkAlgorithm.run(Database database, Relation<O> relation, Relation<NumberVector<?>> radrel) Run the algorithm, with separate radius relation

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type Database

Modifier and Type	Method and Description
protected void	OPTICS.expandClusterOrder(ClusterOrderResult<D> clusterOrder, Database database, RangeQuery<O,D> rangeQuery, DBID objectID, D epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected void	OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected DistanceQuery<V,DoubleDistance>	AbstractProjectedClustering.getDistanceQuery(Database database) Returns the distance function.
C	ClusteringAlgorithm.run(Database database)
ClusterOrderResult<D>	OPTICSTypeAlgorithm.run(Database database)
Clustering<OPTICSModel>	OPTICSXi.run(Database database, Relation<?> relation)
ClusterOrderResult<D>	DeLiClu.run(Database database, Relation<NV> relation)
ClusterOrderResult<D>	OPTICS.run(Database database, Relation<O> relation) Run OPTICS on the database.
Result	SLINK.run(Database database, Relation<O> relation) Performs the SLINK algorithm on the given database.
Clustering<Model>	SNNClustering.run(Database database, Relation<O> relation) Perform SNN clustering
Clustering<MeanModel<V>>	NaiveMeanShiftClustering.run(Database database, Relation<V> relation) Run the mean-shift clustering algorithm.
Clustering<Model>	AbstractProjectedDBSCAN.run(Database database, Relation<V> relation) Run the algorithm
Clustering<EMModel<V>>	EM.run(Database database, Relation<V> relation) Performs the EM clustering algorithm on the given database.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation that return Database

Modifier and Type	Method and Description
private Database	CASH.buildDerivatorDB(Relation<ParameterizationFunction> relation, CASHInterval interval) Builds a database for the derivator consisting of the ids in the specified interval.
private Database	CASH.buildDerivatorDB(Relation<ParameterizationFunction> relation, DBIDs ids) Builds a database for the derivator consisting of the ids in the specified interval.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type Database

Modifier and Type	Method and Description
private Relation<ParameterizationFunction>	CASH.preprocess(Database db, Relation<V> vrel) Preprocess the dataset, precomputing the parameterization functions.
Clustering<Model>	LMCLUS.run(Database database, Relation<NumberVector<?>> relation) The main LMCLUS (Linear manifold clustering algorithm) is processed in this method.
Clustering<Model>	CASH.run(Database database, Relation<V> vrel) Run CASH on the relation.
Clustering<Model>	ORCLUS.run(Database database, Relation<V> relation) Performs the ORCLUS algorithm on the given database.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan with parameters of type Database

Modifier and Type	Method and Description
<T> NeighborPredicate.Instance<T>	EpsilonNeighborPredicate.instantiate(Database database, SimpleTypeInformation<?> type)
<T> NeighborPredicate.Instance<T>	NeighborPredicate.instantiate(Database database, SimpleTypeInformation<?> type) Instantiate for a database.
<T> CorePredicate.Instance<T>	MinPtsCorePredicate.instantiate(Database database, SimpleTypeInformation<?> type)
<T> CorePredicate.Instance<T>	CorePredicate.instantiate(Database database, SimpleTypeInformation<?> type) Instantiate for a database.
Clustering<Model>	GeneralizedDBSCAN.run(Database database)

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with parameters of type Database

Modifier and Type	Method and Description
Clustering<KMeansModel<V>>	KMeansLloyd.run(Database database, Relation<V> relation) Run k-means.
Clustering<MedoidModel>	KMedoidsEM.run(Database database, Relation<V> relation) Run k-medoids
Clustering<KMeansModel<V>>	KMeansMacQueen.run(Database database, Relation<V> relation) Run k-means.
Clustering<MeanModel<V>>	KMediansLloyd.run(Database database, Relation<V> relation) Run k-medians.
Clustering<MedoidModel>	KMedoidsPAM.run(Database database, Relation<V> relation) Run k-medoids

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type Database

Modifier and Type	Method and Description
Clustering<SubspaceModel<V>>	DiSH.run(Database database, Relation<V> relation) Performs the DiSH algorithm on the given database.
Clustering<SubspaceModel<V>>	PROCLUS.run(Database database, Relation<V> relation) Performs the PROCLUS algorithm on the given database.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.clustering.trivial

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.trivial with parameters of type Database

Modifier and Type	Method and Description
Clustering<Model>	ByLabelOrAllInOneClustering.run(Database database)
Clustering<Model>	ByLabelClustering.run(Database database)
Clustering<Model>	ByLabelHierarchicalClustering.run(Database database)

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.outlier

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier with parameters of type Database

Modifier and Type	Method and Description
protected DoubleDataStore	DBOutlierDetection.computeOutlierScores(Database database, Relation<O> relation, D neighborhoodSize)
protected abstract DoubleDataStore	AbstractDBOutlier.computeOutlierScores(Database database, Relation<O> relation, D d) computes an outlier score for each object of the database.
protected DoubleDataStore	DBOutlierScore.computeOutlierScores(Database database, Relation<O> relation, D d)
protected Pair<KNNQuery<O,D>,KNNQuery<O,D>>	LoOP.getKNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN queries for the algorithm.
OutlierResult	OutlierAlgorithm.run(Database database)
OutlierResult	INFLO.run(Database database, Relation<O> relation) Run the algorithm
OutlierResult	LOCI.run(Database database, Relation<O> relation) Run the algorithm
OutlierResult	KNNOutlier.run(Database database, Relation<O> relation) Runs the algorithm in the timed evaluation part.
OutlierResult	HilOut.run(Database database, Relation<O> relation)
OutlierResult	LoOP.run(Database database, Relation<O> relation) Performs the LoOP algorithm on the given database.
OutlierResult	AbstractDBOutlier.run(Database database, Relation<O> relation) Runs the algorithm in the timed evaluation part.
OutlierResult	OPTICSOF.run(Database database, Relation<O> relation) Perform OPTICS-based outlier detection.
OutlierResult	LDOF.run(Database database, Relation<O> relation) Run the algorithm
OutlierResult	KNNWeightOutlier.run(Database database, Relation<O> relation) Runs the algorithm in the timed evaluation part.
OutlierResult	ALOCI.run(Database database, Relation<O> relation)
OutlierResult	SimpleCOP.run(Database database, Relation<V> data)
OutlierResult	EMOutlier.run(Database database, Relation<V> relation) Runs the algorithm in the timed evaluation part.
OutlierResult	AggarwalYuEvolutionary.run(Database database, Relation<V> relation) Performs the evolutionary algorithm on the given database.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.outlier.meta

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.meta with parameters of type Database

Modifier and Type	Method and Description
OutlierResult	RescaleMetaOutlierAlgorithm.run(Database database)
OutlierResult	SimpleOutlierEnsemble.run(Database database)
OutlierResult	ExternalDoubleOutlierScore.run(Database database, Relation<?> relation) Run the algorithm.

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial with parameters of type Database

Modifier and Type	Method and Description
OutlierResult	TrimmedMeanApproach.run(Database database, Relation<N> nrel, Relation<? extends NumberVector<?>> relation) Run the algorithm.
OutlierResult	CTLuZTestOutlier.run(Database database, Relation<N> nrel, Relation<? extends NumberVector<?>> relation) Main method.
OutlierResult	SLOM.run(Database database, Relation<N> spatial, Relation<O> relation)
OutlierResult	SOF.run(Database database, Relation<N> spatial, Relation<O> relation) The main run method

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace that return Database

Modifier and Type	Method and Description
Database	SOD.SODProxyScoreResult.getDatabase()

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with parameters of type Database

Modifier and Type	Method and Description
OutlierResult	OutRankS1.run(Database database)

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.outlier.trivial

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.trivial with parameters of type Database

Modifier and Type	Method and Description
OutlierResult	ByLabelOutlier.run(Database database)
OutlierResult	TrivialGeneratedOutlier.run(Database database)

Uses of Database in de.lmu.ifi.dbs.elki.algorithm.statistics

Methods in de.lmu.ifi.dbs.elki.algorithm.statistics with parameters of type Database

Modifier and Type	Method and Description
Result	AddSingleScale.run(Database database)
HistogramResult<DoubleVector>	AveragePrecisionAtK.run(Database database)
HistogramResult<DoubleVector>	DistanceStatisticsWithClasses.run(Database database)
HistogramResult<DoubleVector>	EvaluateRankingQuality.run(Database database)
HistogramResult<DoubleVector>	RankingQualityHistogram.run(Database database, Relation<O> relation) Process a database

Uses of Database in de.lmu.ifi.dbs.elki.application.cache

Fields in de.lmu.ifi.dbs.elki.application.cache declared as Database

Modifier and Type	Field and Description
private Database	CacheFloatDistanceInOnDiskMatrix.database Holds the database connection to have the algorithm run with.
private Database	CacheFloatDistanceInOnDiskMatrix.Parameterizer.database Holds the database connection to have the algorithm run with.
private Database	CacheDoubleDistanceInOnDiskMatrix.database Holds the database connection to have the algorithm run with.
private Database	CacheDoubleDistanceInOnDiskMatrix.Parameterizer.database Holds the database connection to have the algorithm run with.

Constructors in de.lmu.ifi.dbs.elki.application.cache with parameters of type Database

Constructor and Description
CacheDoubleDistanceInOnDiskMatrix(Database database, DistanceFunction<O,D> distance, File out) Constructor.
CacheFloatDistanceInOnDiskMatrix(Database database, DistanceFunction<O,D> distance, File out) Constructor.

Uses of Database in de.lmu.ifi.dbs.elki.application.greedyensemble

Methods in de.lmu.ifi.dbs.elki.application.greedyensemble with parameters of type Database

Modifier and Type	Method and Description
(package private) void	ComputeKNNOutlierScores.detachResult(Database database, OutlierResult discardresult) Avoid that (future changes?)

Uses of Database in de.lmu.ifi.dbs.elki.application.jsmap

Fields in de.lmu.ifi.dbs.elki.application.jsmap declared as Database

Modifier and Type	Field and Description
private Database	JSONWebServer.db The database we use for obtaining object bundles.

Uses of Database in de.lmu.ifi.dbs.elki.application.visualization

Fields in de.lmu.ifi.dbs.elki.application.visualization declared as Database

Modifier and Type	Field and Description
private Database	KNNExplorer.database Holds the database connection to have the algorithm run with.
protected Database	KNNExplorer.Parameterizer.database
private Database	KNNExplorer.ExplorerWindow.db

Methods in de.lmu.ifi.dbs.elki.application.visualization with parameters of type Database

Modifier and Type	Method and Description
void	KNNExplorer.ExplorerWindow.run(Database db, DistanceQuery<O,D> distanceQuery) Process the given Database and distance function.

Constructors in de.lmu.ifi.dbs.elki.application.visualization with parameters of type Database

Constructor and Description
KNNExplorer(Database database, DistanceFunction<O,D> distanceFunction) Constructor.

Uses of Database in de.lmu.ifi.dbs.elki.database

Subinterfaces of Database in de.lmu.ifi.dbs.elki.database

Modifier and Type	Interface and Description
interface	UpdatableDatabase Database API with updates.

Classes in de.lmu.ifi.dbs.elki.database that implement Database

Modifier and Type	Class and Description
class	AbstractDatabase Abstract base class for database API implementations.
class	HashmapDatabase Provides a mapping for associations based on a Hashtable and functions to get the next usable ID for insertion, making IDs reusable after deletion of the entry.
class	ProxyDatabase A proxy database to use e.g. for projections and partitions.
class	StaticArrayDatabase This database class uses array-based storage and thus does not allow for dynamic insert, delete and update operations.

Methods in de.lmu.ifi.dbs.elki.database with parameters of type Database

Modifier and Type	Method and Description
static <O,D extends Distance<D>> DistanceQuery<O,D>	QueryUtil.getDistanceQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getKNNQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a KNN query object for the given distance function.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getRangeQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a range query object for the given distance function.
static <O,D extends Distance<D>> SimilarityQuery<O,D>	QueryUtil.getSimilarityQuery(Database database, SimilarityFunction<? super O,D> similarityFunction, Object... hints) Get a similarity query, automatically choosing a relation.

Constructors in de.lmu.ifi.dbs.elki.database with parameters of type Database

Constructor and Description
ProxyDatabase(DBIDs ids, Database database) Constructor, proxying all relations of an existing database.

Uses of Database in de.lmu.ifi.dbs.elki.database.relation

Fields in de.lmu.ifi.dbs.elki.database.relation declared as Database

Modifier and Type	Field and Description
private Database	ProxyView.database Our database
private Database	MaterializedRelation.database Our database
private Database	DBIDView.database The database

Methods in de.lmu.ifi.dbs.elki.database.relation that return Database

Modifier and Type	Method and Description
Database	ConvertToStringView.getDatabase()
Database	ProxyView.getDatabase()
Database	MaterializedRelation.getDatabase()
Database	DBIDView.getDatabase()
Database	ProjectedView.getDatabase()
Database	Relation.getDatabase() Get the associated database.

Methods in de.lmu.ifi.dbs.elki.database.relation with parameters of type Database

Modifier and Type	Method and Description
static <O> ProxyView<O>	ProxyView.wrap(Database database, DBIDs idview, Relation<O> inner) Constructor-like static method.

Constructors in de.lmu.ifi.dbs.elki.database.relation with parameters of type Database

Constructor and Description
DBIDView(Database database, DBIDs ids) Constructor.
MaterializedRelation(Database database, SimpleTypeInformation<O> type, DBIDs ids) Constructor.
MaterializedRelation(Database database, SimpleTypeInformation<O> type, DBIDs ids, String name) Constructor.
MaterializedRelation(Database database, SimpleTypeInformation<O> type, DBIDs ids, String name, DataStore<O> content) Constructor.
ProxyView(Database database, DBIDs idview, Relation<O> inner) Constructor.

Uses of Database in de.lmu.ifi.dbs.elki.evaluation.histogram

Methods in de.lmu.ifi.dbs.elki.evaluation.histogram with parameters of type Database

Modifier and Type	Method and Description
HistogramResult<DoubleVector>	ComputeOutlierHistogram.evaluateOutlierResult(Database database, OutlierResult or) Evaluate a single outlier result as histogram.

Uses of Database in de.lmu.ifi.dbs.elki.result

Methods in de.lmu.ifi.dbs.elki.result that return Database

Modifier and Type	Method and Description
static Database	ResultUtil.findDatabase(Result baseResult) Find the first database result in the tree.

Methods in de.lmu.ifi.dbs.elki.result with parameters of type Database

Modifier and Type	Method and Description
static <O> void	ResultUtil.ensureClusteringResult(Database db, Result result) Ensure that the result contains at least one Clustering.
static SelectionResult	ResultUtil.ensureSelectionResult(Database db) Ensure that there also is a selection container object.
private void	KMLOutputHandler.writeKMLData(XMLStreamWriter out, OutlierResult outlierResult, Database database)

Uses of Database in de.lmu.ifi.dbs.elki.result.optics

Methods in de.lmu.ifi.dbs.elki.result.optics that return Database

Modifier and Type	Method and Description
Database	ClusterOrderResult.ReachabilityDistanceAdapter.getDatabase()
Database	ClusterOrderResult.PredecessorAdapter.getDatabase()

Uses of Database in de.lmu.ifi.dbs.elki.result.textwriter

Methods in de.lmu.ifi.dbs.elki.result.textwriter with parameters of type Database

Modifier and Type	Method and Description
void	TextWriter.output(Database db, Result r, StreamFactory streamOpener) Stream output.
private void	TextWriter.printObject(TextWriterStream out, Database db, DBIDRef objID, List<Relation<?>> ra)
private void	TextWriter.writeClusterResult(Database db, StreamFactory streamOpener, Cluster<?> clus, List<Relation<?>> ra, NamingScheme naming, List<SettingsResult> sr)
private void	TextWriter.writeOrderingResult(Database db, StreamFactory streamOpener, OrderingResult or, List<Relation<?>> ra, List<SettingsResult> sr)

Uses of Database in de.lmu.ifi.dbs.elki.utilities

Methods in de.lmu.ifi.dbs.elki.utilities with parameters of type Database

Modifier and Type	Method and Description
static SortedSet<ClassLabel>	DatabaseUtil.getClassLabels(Database database) Retrieves all class labels within the database.
static ArrayModifiableDBIDs	DatabaseUtil.getObjectsByLabelMatch(Database database, Pattern name_pattern) Find object by matching their labels.
static Relation<String>	DatabaseUtil.guessLabelRepresentation(Database database) Guess a potentially label-like representation, preferring class labels.
static Relation<String>	DatabaseUtil.guessObjectLabelRepresentation(Database database) Guess a potentially object label-like representation.

Uses of Database in de.lmu.ifi.dbs.elki.visualization

Methods in de.lmu.ifi.dbs.elki.visualization with parameters of type Database

Modifier and Type	Method and Description
static String	VisualizerParameterizer.getTitle(Database db, Result result) Try to automatically generate a title for this.

Uses of Database in de.lmu.ifi.dbs.elki.visualization.gui

Fields in de.lmu.ifi.dbs.elki.visualization.gui declared as Database

Modifier and Type	Field and Description
(package private) Database	SelectionTableWindow.database The database we use

Uses of Database in de.lmu.ifi.dbs.elki.workflow

Fields in de.lmu.ifi.dbs.elki.workflow declared as Database

Modifier and Type	Field and Description
private Database	InputStep.database Holds the database to have the algorithms run with.
protected Database	InputStep.Parameterizer.database Holds the database to have the algorithms run on.

Methods in de.lmu.ifi.dbs.elki.workflow that return Database

Modifier and Type	Method and Description
Database	InputStep.getDatabase() Get the database to use.

Methods in de.lmu.ifi.dbs.elki.workflow with parameters of type Database

Modifier and Type	Method and Description
HierarchicalResult	AlgorithmStep.runAlgorithms(Database database) Run algorithms.
void	EvaluationStep.runEvaluators(HierarchicalResult r, Database db)

Constructors in de.lmu.ifi.dbs.elki.workflow with parameters of type Database

Constructor and Description
InputStep(Database database) Constructor.

Uses of Database in tutorial.clustering

Methods in tutorial.clustering with parameters of type Database

Modifier and Type	Method and Description
Clustering<MeanModel<V>>	SameSizeKMeansAlgorithm.run(Database database, Relation<V> relation) Run k-means with cluster size constraints.

Uses of Database in tutorial.outlier

Methods in tutorial.outlier with parameters of type Database

Modifier and Type	Method and Description
OutlierResult	DistanceStddevOutlier.run(Database database, Relation<O> relation) Run the outlier detection algorithm