Uses of Interface
de.lmu.ifi.dbs.elki.result.Result

Packages that use Result

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.classification	Classification algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.clustering.optics	OPTICS family of clustering algorithms.
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.uncertain	Clustering algorithms for uncertain data.
de.lmu.ifi.dbs.elki.algorithm.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.projection	Data projections (see also preprocessing filters for basic projections).
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms.
de.lmu.ifi.dbs.elki.algorithm.timeseries	Algorithms for change point detection in time series.
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	Cluster models classes for various algorithms
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	Functionality for the evaluation of algorithms.
de.lmu.ifi.dbs.elki.evaluation.classification	Evaluation of classification algorithms.
de.lmu.ifi.dbs.elki.evaluation.clustering	Evaluation of clustering results
de.lmu.ifi.dbs.elki.evaluation.clustering.extractor	Classes to extract clusterings from hierarchical clustering.
de.lmu.ifi.dbs.elki.evaluation.clustering.internal	Internal evaluation measures for clusterings.
de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments	Pair-segment analysis of multiple clusterings
de.lmu.ifi.dbs.elki.evaluation.index	Simple index evaluation methods
de.lmu.ifi.dbs.elki.evaluation.outlier	Evaluate an outlier score using a misclassification based cost model
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.distancematrix	Precomputed distance matrix.
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	Indexes using inverted lists.
de.lmu.ifi.dbs.elki.index.lsh	Locality Sensitive Hashing
de.lmu.ifi.dbs.elki.index.preprocessed	Index structure based on preprocessors
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA
de.lmu.ifi.dbs.elki.index.preprocessed.preference	Indexes storing preference vectors
de.lmu.ifi.dbs.elki.index.preprocessed.snn	Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.projected	Projected indexes for data
de.lmu.ifi.dbs.elki.index.tree	Tree-based index structures
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	Cover-tree variations.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants	M-Tree and variants
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	MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab	MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.index.tree.spatial	Tree-based index structures for spatial indexing
de.lmu.ifi.dbs.elki.index.tree.spatial.kd	K-d-tree and variants
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants	R*-Tree and variants
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat	FlatRStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	RStarTree
de.lmu.ifi.dbs.elki.index.vafile	Vector Approximation File
de.lmu.ifi.dbs.elki.math.geometry	Algorithms from computational geometry
de.lmu.ifi.dbs.elki.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.outlier	Outlier result classes
de.lmu.ifi.dbs.elki.result.textwriter	Text serialization (CSV, Gnuplot, Console, ...)
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.visualization.gui.detail	Classes for managing a detail view
de.lmu.ifi.dbs.elki.visualization.gui.overview	Classes for managing the overview plot
de.lmu.ifi.dbs.elki.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.parallel3d	3DPC: 3D parallel coordinate plot visualization for ELKI.
de.lmu.ifi.dbs.elki.visualization.visualizers	Visualizers for various results
de.lmu.ifi.dbs.elki.visualization.visualizers.histogram	Visualizers based on 1D projected histograms
de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments	Visualizers for inspecting cluster differences using pair counting segments
de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs	Thumbnail "Visualizers" (that take care of refreshing thumbnails)
de.lmu.ifi.dbs.elki.workflow	Work flow packages, e.g., following the usual KDD model.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation
tutorial.outlier	Tutorials on implementing outlier detection methods in ELKI.

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

Classes in de.lmu.ifi.dbs.elki.algorithm with type parameters of type Result

Modifier and Type	Class and Description
class	AbstractAlgorithm<R extends Result> This class serves also as a model of implementing an algorithm within this framework.
class	AbstractDistanceBasedAlgorithm<O,R extends Result> Abstract base class for distance-based algorithms.
class	AbstractNumberVectorDistanceBasedAlgorithm<O,R extends Result> Abstract base class for distance-based algorithms that need to work with synthetic numerical vectors such as mean vectors.
class	AbstractPrimitiveDistanceBasedAlgorithm<O,R extends Result> Abstract base class for distance-based algorithms that need to work with synthetic objects such as mean vectors.

Classes in de.lmu.ifi.dbs.elki.algorithm that implement Result

Modifier and Type	Class and Description
static class	KNNDistancesSampler.KNNDistanceOrderResult Curve result for a list containing the knn distances.

Methods in de.lmu.ifi.dbs.elki.algorithm that return Result

Modifier and Type	Method and Description
Result	NullAlgorithm.run(Database database)
Result	Algorithm.run(Database database) Runs the algorithm.
Result	DummyAlgorithm.run(Database database, Relation<O> relation) Run the algorithm.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.benchmark that return Result

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	ValidateApproximativeKNNIndex.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 Result in de.lmu.ifi.dbs.elki.algorithm.classification

Classes in de.lmu.ifi.dbs.elki.algorithm.classification with type parameters of type Result

Modifier and Type	Class and Description
class	AbstractClassifier<O,R extends Result> Abstract base class for algorithms.

Methods in de.lmu.ifi.dbs.elki.algorithm.classification that return Result

Modifier and Type	Method and Description
Result	KNNClassifier.run(Database database) Deprecated.

Uses of Result in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical with type parameters of type Result

Modifier and Type	Class and Description
class	AbstractHDBSCAN<O,R extends Result> Abstract base class for HDBSCAN variations.

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical that implement Result

Modifier and Type	Class and Description
class	PointerDensityHierarchyRepresentationResult Extended pointer representation useful for HDBSCAN.
class	PointerHierarchyRepresentationResult The pointer representation of a hierarchical clustering.
class	PointerPrototypeHierarchyRepresentationResult Hierarchical clustering with prototypes (used by MiniMax).

Uses of Result in de.lmu.ifi.dbs.elki.algorithm.clustering.optics

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.optics that implement Result

Modifier and Type	Class and Description
class	ClusterOrder Class to store the result of an ordering clustering algorithm such as OPTICS.
class	CorrelationClusterOrder Cluster order entry for correlation-based OPTICS variants.
static class	OPTICSXi.SteepAreaResult Result containing the chi-steep areas.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that implement Result

Modifier and Type	Class and Description
static class	DiSH.DiSHClusterOrder DiSH cluster order.

Uses of Result in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain that implement Result

Modifier and Type	Class and Description
static class	RepresentativeUncertainClustering.RepresentativenessEvaluation Representativeness evaluation result.

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

Modifier and Type	Method and Description
protected Clustering<?>	RepresentativeUncertainClustering.runClusteringAlgorithm(ResultHierarchy hierarchy, Result parent, DBIDs ids, DataStore<DoubleVector> store, int dim, java.lang.String title) Run a clustering algorithm on a single instance.
protected C	CenterOfMassMetaClustering.runClusteringAlgorithm(ResultHierarchy hierarchy, Result parent, DBIDs ids, DataStore<DoubleVector> store, int dim, java.lang.String title) Run a clustering algorithm on a single instance.

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

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

Modifier and Type	Method and Description
private OutlierResult	RescaleMetaOutlierAlgorithm.getOutlierResult(ResultHierarchy hier, Result result) Find an OutlierResult to work with.

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

Subinterfaces of Result in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Modifier and Type	Interface and Description
interface	NeighborSetPredicate Predicate to obtain the neighbors of a reference object as set.

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood that implement Result

Modifier and Type	Class and Description
class	AbstractPrecomputedNeighborhood Abstract base class for precomputed neighborhoods.
class	ExtendedNeighborhood Neighborhood obtained by computing the k-fold closure of an existing neighborhood.
class	ExternalNeighborhood A precomputed neighborhood, loaded from an external file.
class	PrecomputedKNearestNeighborNeighborhood Neighborhoods based on k nearest neighbors.

Uses of Result in de.lmu.ifi.dbs.elki.algorithm.projection

Classes in de.lmu.ifi.dbs.elki.algorithm.projection with type parameters of type Result

Modifier and Type	Class and Description
class	AbstractProjectionAlgorithm<R extends Result> Abstract base class for projection algorithms.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.statistics that implement Result

Modifier and Type	Class and Description
static class	EvaluateRetrievalPerformance.RetrievalPerformanceResult Result object for MAP scores.

Methods in de.lmu.ifi.dbs.elki.algorithm.statistics that return Result

Modifier and Type	Method and Description
Result	AddUniformScale.run(Database database)
Result	AddSingleScale.run(Database database)
Result	HopkinsStatisticClusteringTendency.run(Database database, Relation<NumberVector> relation) Runs the algorithm in the timed evaluation part.
Result	EstimateIntrinsicDimensionality.run(Database database, Relation<O> relation)
Result	RangeQuerySelectivity.run(Database database, Relation<V> relation)

Uses of Result in de.lmu.ifi.dbs.elki.algorithm.timeseries

Classes in de.lmu.ifi.dbs.elki.algorithm.timeseries that implement Result

Modifier and Type	Class and Description
class	ChangePoints Change point detection result Used by change or trend detection algorithms TODO: we need access to the data labels / timestamp information!

Uses of Result in de.lmu.ifi.dbs.elki.data

Classes in de.lmu.ifi.dbs.elki.data that implement Result

Modifier and Type	Class and Description
class	Clustering<M extends Model> Result class for clusterings.

Methods in de.lmu.ifi.dbs.elki.data with parameters of type Result

Modifier and Type	Method and Description
static java.util.List<Clustering<? extends Model>>	Clustering.getClusteringResults(Result r) Collect all clustering results from a Result

Uses of Result in de.lmu.ifi.dbs.elki.data.model

Classes in de.lmu.ifi.dbs.elki.data.model that implement Result

Modifier and Type	Class and Description
class	CorrelationAnalysisSolution<V extends NumberVector> A solution of correlation analysis is a matrix of equations describing the dependencies.

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

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

Modifier and Type	Interface and Description
interface	Database Database specifies the requirements for any database implementation.
interface	UpdatableDatabase Database API with updates.

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

Modifier and Type	Class and Description
class	AbstractDatabase Abstract base class for database API implementations.
class	HashmapDatabase Database storing data using hashtable storage, and thus allowing additional and removal of objects.
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 Result

Modifier and Type	Method and Description
void	DatabaseEventManager.fireResultAdded(Result r, Result parent) Informs all registered ResultListener that a new result was added.
void	DatabaseEventManager.fireResultRemoved(Result r, Result parent) Informs all registered ResultListener that a new result has been removed.

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

Subinterfaces of Result in de.lmu.ifi.dbs.elki.database.relation

Modifier and Type	Interface and Description
interface	DoubleRelation Interface for double-valued relations.
interface	ModifiableRelation<O> Relations that allow modification.
interface	Relation<O> An object representation from a database.

Classes in de.lmu.ifi.dbs.elki.database.relation that implement Result

Modifier and Type	Class and Description
class	AbstractRelation<O> Abstract base class for relations.
class	ConvertToStringView Representation adapter that uses toString() to produce a string representation.
class	DBIDView Pseudo-representation that is the object ID itself.
class	MaterializedDoubleRelation Represents a single representation.
class	MaterializedRelation<O> Represents a single representation.
class	ProjectedView<IN,OUT> Projected relation view (non-materialized)
class	ProxyView<O> A virtual partitioning of the database.

Uses of Result in de.lmu.ifi.dbs.elki.evaluation

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

Modifier and Type	Method and Description
protected void	AutomaticEvaluation.autoEvaluateClusterings(ResultHierarchy hier, Result newResult)
protected void	AutomaticEvaluation.autoEvaluateOutliers(ResultHierarchy hier, Result newResult)
static void	AutomaticEvaluation.ensureClusteringResult(Database db, Result result) Ensure that the result contains at least one Clustering.
void	NoAutomaticEvaluation.processNewResult(ResultHierarchy hier, Result newResult)
void	AutomaticEvaluation.processNewResult(ResultHierarchy hier, Result newResult)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.classification

Classes in de.lmu.ifi.dbs.elki.evaluation.classification that implement Result

Modifier and Type	Class and Description
class	ConfusionMatrixEvaluationResult Provides the prediction performance measures for a classifier based on the confusion matrix.

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.clustering

Classes in de.lmu.ifi.dbs.elki.evaluation.clustering that implement Result

Modifier and Type	Class and Description
static class	EvaluateClustering.ScoreResult Result object for outlier score judgements.

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering with parameters of type Result

Modifier and Type	Method and Description
void	EvaluateClustering.processNewResult(ResultHierarchy hier, Result newResult)
void	LogClusterSizes.processNewResult(ResultHierarchy hier, Result result)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor with parameters of type Result

Modifier and Type	Method and Description
void	SimplifiedHierarchyExtractionEvaluator.processNewResult(ResultHierarchy hier, Result newResult)
void	HDBSCANHierarchyExtractionEvaluator.processNewResult(ResultHierarchy hier, Result newResult)
void	CutDendrogramByNumberOfClustersExtractor.processNewResult(ResultHierarchy hier, Result newResult)
void	CutDendrogramByHeightExtractor.processNewResult(ResultHierarchy hier, Result newResult)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.internal with parameters of type Result

Modifier and Type	Method and Description
void	EvaluateSquaredErrors.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateDBCV.processNewResult(ResultHierarchy hier, Result newResult)
void	EvaluateConcordantPairs.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateCIndex.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateVarianceRatioCriteria.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateSimplifiedSilhouette.processNewResult(ResultHierarchy hier, Result result)
void	EvaluatePBMIndex.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateSilhouette.processNewResult(ResultHierarchy hier, Result result)
void	EvaluateDaviesBouldin.processNewResult(ResultHierarchy hier, Result result)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments

Classes in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments that implement Result

Modifier and Type	Class and Description
class	Segments Creates segments of two or more clusterings.

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments with parameters of type Result

Modifier and Type	Method and Description
void	ClusterPairSegmentAnalysis.processNewResult(ResultHierarchy hier, Result result) Perform clusterings evaluation

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.index

Classes in de.lmu.ifi.dbs.elki.evaluation.index that implement Result

Modifier and Type	Class and Description
class	IndexStatistics.IndexMetaResult Result class.

Methods in de.lmu.ifi.dbs.elki.evaluation.index with parameters of type Result

Modifier and Type	Method and Description
void	IndexStatistics.processNewResult(ResultHierarchy hier, Result newResult)
void	IndexPurity.processNewResult(ResultHierarchy hier, Result newResult)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.outlier

Classes in de.lmu.ifi.dbs.elki.evaluation.outlier that implement Result

Modifier and Type	Class and Description
class	JudgeOutlierScores.ScoreResult Result object for outlier score judgements.
static class	OutlierPrecisionAtKCurve.PrecisionAtKCurve Precision at K curve.
static class	OutlierPrecisionRecallCurve.PRCurve P/R Curve
static class	OutlierROCCurve.ROCResult Result object for ROC curves.
static class	OutlierSmROCCurve.SmROCResult Result object for Smooth ROC curves.

Methods in de.lmu.ifi.dbs.elki.evaluation.outlier with parameters of type Result

Modifier and Type	Method and Description
void	OutlierThresholdClustering.processNewResult(ResultHierarchy hier, Result newResult)
void	OutlierPrecisionAtKCurve.processNewResult(ResultHierarchy hier, Result result)
void	OutlierROCCurve.processNewResult(ResultHierarchy hier, Result result)
void	OutlierSmROCCurve.processNewResult(ResultHierarchy hier, Result result)
void	ComputeOutlierHistogram.processNewResult(ResultHierarchy hier, Result newResult)
void	OutlierPrecisionRecallCurve.processNewResult(ResultHierarchy hier, Result result)
void	JudgeOutlierScores.processNewResult(ResultHierarchy hier, Result result)
void	OutlierRankingEvaluation.processNewResult(ResultHierarchy hier, Result result)

Uses of Result in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix

Classes in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix that implement Result

Modifier and Type	Class and Description
static class	ComputeSimilarityMatrixImage.SimilarityMatrix Similarity matrix image.

Methods in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix with parameters of type Result

Modifier and Type	Method and Description
void	ComputeSimilarityMatrixImage.processNewResult(ResultHierarchy hier, Result result)

Uses of Result in de.lmu.ifi.dbs.elki.index

Subinterfaces of Result in de.lmu.ifi.dbs.elki.index

Modifier and Type	Interface and Description
interface	DistanceIndex<O> Index with support for distance queries (e.g. precomputed distance matrixes, caches)
interface	DynamicIndex Index that supports dynamic insertions and removals.
interface	Index Interface defining the minimum requirements for all index classes.
interface	KNNIndex<O> Index with support for kNN queries.
interface	RangeIndex<O> Index with support for range queries (radius queries).
interface	RKNNIndex<O> Index with support for kNN queries.
interface	SimilarityIndex<O> Index with support for similarity queries (e.g. precomputed similarity matrixes, caches)
interface	SimilarityRangeIndex<O> Index with support for similarity range queries.

Classes in de.lmu.ifi.dbs.elki.index that implement Result

Modifier and Type	Class and Description
class	AbstractIndex<O> Abstract base class for indexes with some implementation defaults.
class	AbstractRefiningIndex<O> Abstract base class for Filter-refinement indexes.

Uses of Result in de.lmu.ifi.dbs.elki.index.distancematrix

Classes in de.lmu.ifi.dbs.elki.index.distancematrix that implement Result

Modifier and Type	Class and Description
class	PrecomputedDistanceMatrix<O> Distance matrix, for precomputing similarity for a small data set.
class	PrecomputedSimilarityMatrix<O> Precomputed similarity matrix, for a small data set.

Uses of Result in de.lmu.ifi.dbs.elki.index.idistance

Classes in de.lmu.ifi.dbs.elki.index.idistance that implement Result

Modifier and Type	Class and Description
class	InMemoryIDistanceIndex<O> In-memory iDistance index, a metric indexing method using a reference point embedding.

Uses of Result in de.lmu.ifi.dbs.elki.index.invertedlist

Classes in de.lmu.ifi.dbs.elki.index.invertedlist that implement Result

Modifier and Type	Class and Description
class	InMemoryInvertedIndex<V extends NumberVector> Simple index using inverted lists, for cosine distance only.

Uses of Result in de.lmu.ifi.dbs.elki.index.lsh

Classes in de.lmu.ifi.dbs.elki.index.lsh that implement Result

Modifier and Type	Class and Description
class	InMemoryLSHIndex.Instance Instance of a LSH index for a single relation.

Uses of Result in de.lmu.ifi.dbs.elki.index.preprocessed

Classes in de.lmu.ifi.dbs.elki.index.preprocessed that implement Result

Modifier and Type	Class and Description
class	AbstractPreprocessorIndex<O,R> Abstract base class for simple preprocessor based indexes, requiring a simple object storage for preprocessing results.

Uses of Result in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.knn that implement Result

Modifier and Type	Class and Description
class	AbstractMaterializeKNNPreprocessor<O> Abstract base class for KNN Preprocessors.
class	CachedDoubleDistanceKNNPreprocessor<O> Preprocessor that loads an existing cached kNN result.
class	KNNJoinMaterializeKNNPreprocessor<V extends NumberVector> Class to materialize the kNN using a spatial join on an R-tree.
class	MaterializeKNNAndRKNNPreprocessor<O> A preprocessor for annotation of the k nearest neighbors and the reverse k nearest neighbors (and their distances) to each database object.
class	MaterializeKNNPreprocessor<O> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	NaiveProjectedKNNPreprocessor<O extends NumberVector> Compute the approximate k nearest neighbors using 1 dimensional projections.
class	NNDescent<O> NN-desent (also known as KNNGraph) is an approximate nearest neighbor search algorithm beginning with a random sample, then iteratively refining this sample until.
class	PartitionApproximationMaterializeKNNPreprocessor<O> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	RandomSampleKNNPreprocessor<O> Class that computed the kNN only on a random sample.
class	SpacefillingKNNPreprocessor<O extends NumberVector> Compute the nearest neighbors approximatively using space filling curves.
class	SpacefillingMaterializeKNNPreprocessor<O extends NumberVector> Compute the nearest neighbors approximatively using space filling curves.
class	SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends SpatialNode<N,E>,E extends SpatialEntry> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.

Uses of Result in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Subinterfaces of Result in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Modifier and Type	Interface and Description
interface	FilteredLocalPCAIndex<NV extends NumberVector> Interface for an index providing local PCA results.

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.localpca that implement Result

Modifier and Type	Class and Description
class	AbstractFilteredPCAIndex<NV extends NumberVector> Abstract base class for a local PCA based index.
class	KNNQueryFilteredPCAIndex<NV extends NumberVector> Provides the local neighborhood to be considered in the PCA as the k nearest neighbors of an object.

Uses of Result in de.lmu.ifi.dbs.elki.index.preprocessed.preference

Subinterfaces of Result in de.lmu.ifi.dbs.elki.index.preprocessed.preference

Modifier and Type	Interface and Description
interface	PreferenceVectorIndex<NV extends NumberVector> Interface for an index providing preference vectors.

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.preference that implement Result

Modifier and Type	Class and Description
class	AbstractPreferenceVectorIndex<NV extends NumberVector> Abstract base class for preference vector based algorithms.
class	DiSHPreferenceVectorIndex<V extends NumberVector> Preprocessor for DiSH preference vector assignment to objects of a certain database.
class	HiSCPreferenceVectorIndex<V extends NumberVector> Preprocessor for HiSC preference vector assignment to objects of a certain database.

Uses of Result in de.lmu.ifi.dbs.elki.index.preprocessed.snn

Subinterfaces of Result in de.lmu.ifi.dbs.elki.index.preprocessed.snn

Modifier and Type	Interface and Description
interface	SharedNearestNeighborIndex<O> Interface for an index providing nearest neighbor sets.

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.snn that implement Result

Modifier and Type	Class and Description
class	SharedNearestNeighborPreprocessor<O> A preprocessor for annotation of the ids of nearest neighbors to each database object.

Uses of Result in de.lmu.ifi.dbs.elki.index.projected

Classes in de.lmu.ifi.dbs.elki.index.projected that implement Result

Modifier and Type	Class and Description
class	LatLngAsECEFIndex<O extends NumberVector> Index a 2d data set (consisting of Lat/Lng pairs) by using a projection to 3D coordinates (WGS-86 to ECEF).
class	LngLatAsECEFIndex<O extends NumberVector> Index a 2d data set (consisting of Lng/Lat pairs) by using a projection to 3D coordinates (WGS-86 to ECEF).
class	ProjectedIndex<O,I> Class to index data in an arbitrary projection only.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree

Classes in de.lmu.ifi.dbs.elki.index.tree that implement Result

Modifier and Type	Class and Description
class	IndexTree<N extends Node<E>,E extends Entry> Abstract super class for all tree based index classes.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical that implement Result

Modifier and Type	Class and Description
class	MetricalIndexTree<O,N extends Node<E>,E extends Entry> Abstract super class for all metrical index classes.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree that implement Result

Modifier and Type	Class and Description
class	AbstractCoverTree<O> Abstract base class for cover tree variants.
class	CoverTree<O> Cover tree data structure (in-memory).
class	SimplifiedCoverTree<O> Simplified cover tree data structure (in-memory).

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants that implement Result

Modifier and Type	Class and Description
class	AbstractMTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>> Abstract super class for all M-Tree variants.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees that implement Result

Modifier and Type	Class and Description
class	AbstractMkTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>> Abstract class for all M-Tree variants supporting processing of reverse k-nearest neighbor queries by using the k-nn distances of the entries, where k is less than or equal to the given parameter.
class	AbstractMkTreeUnified<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MkTreeSettings<O,N,E>> Abstract class for all M-Tree variants supporting processing of reverse k-nearest neighbor queries by using the k-nn distances of the entries, where k is less than or equal to the given parameter.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp that implement Result

Modifier and Type	Class and Description
class	MkAppTree<O> MkAppTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
class	MkAppTreeIndex<O> MkAppTree used as database index.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop that implement Result

Modifier and Type	Class and Description
class	MkCoPTree<O> MkCopTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
class	MkCoPTreeIndex<O> MkCoPTree used as database index.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax that implement Result

Modifier and Type	Class and Description
class	MkMaxTree<O> MkMaxTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k <= k_max.
class	MkMaxTreeIndex<O> MkMax tree

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab that implement Result

Modifier and Type	Class and Description
class	MkTabTree<O> MkTabTree is a metrical index structure based on the concepts of the M-Tree supporting efficient processing of reverse k nearest neighbor queries for parameter k < kmax.
class	MkTabTreeIndex<O> MkTabTree used as database index.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree that implement Result

Modifier and Type	Class and Description
class	MTree<O> MTree is a metrical index structure based on the concepts of the M-Tree.
class	MTreeIndex<O> Class for using an m-tree as database index.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial that implement Result

Modifier and Type	Class and Description
class	SpatialIndexTree<N extends SpatialNode<N,E>,E extends SpatialEntry> Abstract super class for all spatial index tree classes.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.kd

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.kd that implement Result

Modifier and Type	Class and Description
class	MinimalisticMemoryKDTree<O extends NumberVector> Simple implementation of a static in-memory K-D-tree.
class	SmallMemoryKDTree<O extends NumberVector> Simple implementation of a static in-memory K-D-tree.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants that implement Result

Modifier and Type	Class and Description
class	AbstractRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends RTreeSettings> Abstract superclass for index structures based on a R*-Tree.
class	NonFlatRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends RTreeSettings> Abstract superclass for all non-flat R*-Tree variants.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu that implement Result

Modifier and Type	Class and Description
class	DeLiCluTree DeLiCluTree is a spatial index structure based on an R-Tree.
class	DeLiCluTreeIndex<O extends NumberVector> The common use of the DeLiClu tree: indexing number vectors.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat that implement Result

Modifier and Type	Class and Description
class	FlatRStarTree FlatRTree is a spatial index structure based on a R*-Tree but with a flat directory.
class	FlatRStarTreeIndex<O extends NumberVector> The common use of the flat rstar tree: indexing number vectors.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn that implement Result

Modifier and Type	Class and Description
class	RdKNNTree<O extends NumberVector> RDkNNTree is a spatial index structure based on the concepts of the R*-Tree supporting efficient processing of reverse k nearest neighbor queries.

Uses of Result in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar that implement Result

Modifier and Type	Class and Description
class	RStarTree RStarTree is a spatial index structure based on the concepts of the R*-Tree.
class	RStarTreeIndex<O extends NumberVector> The common use of the rstar tree: indexing number vectors.

Uses of Result in de.lmu.ifi.dbs.elki.index.vafile

Classes in de.lmu.ifi.dbs.elki.index.vafile that implement Result

Modifier and Type	Class and Description
class	PartialVAFile<V extends NumberVector> PartialVAFile.
class	VAFile<V extends NumberVector> Vector-approximation file (VAFile) Reference: R.

Uses of Result in de.lmu.ifi.dbs.elki.math.geometry

Classes in de.lmu.ifi.dbs.elki.math.geometry that implement Result

Modifier and Type	Class and Description
class	XYCurve An XYCurve is an ordered collection of 2d points, meant for chart generation.
class	XYPlot An XYCurve is an ordered collection of 2d XYPlot.Curves, meant for chart generation.

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

Subinterfaces of Result in de.lmu.ifi.dbs.elki.result

Modifier and Type	Interface and Description
interface	HierarchicalResult Result with an internal hierarchy.
interface	IterableResult<O> Interface of an "iterable" result (e.g. a list, table) that can be printed one-by-one.
interface	OrderingResult Interface for a result providing an object ordering.
interface	PixmapResult Result encapsulating a single image.

Classes in de.lmu.ifi.dbs.elki.result that implement Result

Modifier and Type	Class and Description
class	AbstractHierarchicalResult Abstract class for a result object with hierarchy
class	AssociationRuleResult Result class for association rule mining
class	BasicResult Basic class for a result.
class	CollectionResult<O> Simple 'collection' type of result.
class	EvaluationResult Abstract evaluation result.
class	FrequentItemsetsResult Result class for frequent itemset mining algorithms.
class	HistogramResult Histogram result.
class	OrderingFromDataStore<T extends java.lang.Comparable<T>> Result class providing an ordering backed by a hashmap.
class	ReferencePointsResult<O> Result used in passing the reference points to the visualizers.
class	SamplingResult Wrapper for storing the current database sample.
class	ScalesResult Class to keep shared scales across visualizers.
class	SelectionResult Selection result wrapper.
class	SettingsResult Result that keeps track of settings that were used in generating this particular result.

Fields in de.lmu.ifi.dbs.elki.result declared as Result

Modifier and Type	Field and Description
(package private) Result	ExportVisualizations.baseResult Base result

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

Modifier and Type	Method and Description
static <C extends Result> java.util.ArrayList<C>	ResultUtil.filterResults(ResultHierarchy hier, java.lang.Class<? super C> restrictionClass) Return only results of the given restriction class
static <C extends Result> java.util.ArrayList<C>	ResultUtil.filterResults(ResultHierarchy hier, Result r, java.lang.Class<? super C> restrictionClass) Return only results of the given restriction class

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

Modifier and Type	Method and Description
boolean	ResultHierarchy.add(Result parent, Result child)
static void	ResultUtil.addChildResult(HierarchicalResult parent, Result child) Add a child result.
void	AbstractHierarchicalResult.addChildResult(Result child) Add a child result.
static <C extends Result> java.util.ArrayList<C>	ResultUtil.filterResults(ResultHierarchy hier, Result r, java.lang.Class<? super C> restrictionClass) Return only results of the given restriction class
static Database	ResultUtil.findDatabase(ResultHierarchy hier, Result baseResult) Find the first database result in the tree.
static EvaluationResult	EvaluationResult.findOrCreate(ResultHierarchy hierarchy, Result parent, java.lang.String name, java.lang.String shortname) Find or create an evaluation result.
private void	ResultHierarchy.fireResultAdded(Result child, Result parent) Informs all registered ResultListener that a new result was added.
private void	ResultHierarchy.fireResultChanged(Result current) Informs all registered ResultListener that a result has changed.
private void	ResultHierarchy.fireResultRemoved(Result child, Result parent) Informs all registered ResultListener that a new result has been removed.
static java.util.List<CollectionResult<?>>	ResultUtil.getCollectionResults(Result r) Collect all collection results from a Result
static java.util.List<IterableResult<?>>	ResultUtil.getIterableResults(Result r) Return all Iterable results
static java.util.List<OrderingResult>	ResultUtil.getOrderingResults(Result r) Collect all ordering results from a Result
static java.util.List<Relation<?>>	ResultUtil.getRelations(Result r) Collect all Annotation results from a Result
static java.util.List<SettingsResult>	SettingsResult.getSettingsResults(Result r) Collect all settings results from a Result
void	LogResultStructureResultHandler.processNewResult(ResultHierarchy hier, Result newResult)
void	DiscardResultHandler.processNewResult(ResultHierarchy hier, Result newResult)
void	ResultWriter.processNewResult(ResultHierarchy hier, Result result)
void	KMLOutputHandler.processNewResult(ResultHierarchy hier, Result newResult)
void	AutomaticVisualization.processNewResult(ResultHierarchy hier, Result result)
void	ExportVisualizations.processNewResult(ResultHierarchy hier, Result newResult)
void	ClusteringVectorDumper.processNewResult(ResultHierarchy hier, Result newResult)
void	ResultProcessor.processNewResult(ResultHierarchy hier, Result newResult) Process a result.
private void	LogResultStructureResultHandler.recursiveLogResult(java.lang.StringBuilder buf, Hierarchy<Result> hier, Result result, int depth) Recursively walk through the result tree.
boolean	ResultHierarchy.remove(Result parent, Result child)
static void	ResultUtil.removeRecursive(ResultHierarchy hierarchy, Result child) Recursively remove a result and its children.
void	ResultListener.resultAdded(Result child, Result parent) A new derived result was added.
void	ResultListener.resultChanged(Result current) Notify that the current result has changed substantially.
void	ResultHierarchy.resultChanged(Result res) Signal that a result has changed (public API)
void	ResultListener.resultRemoved(Result child, Result parent) A result was removed.

Method parameters in de.lmu.ifi.dbs.elki.result with type arguments of type Result

Modifier and Type	Method and Description
private void	LogResultStructureResultHandler.recursiveLogResult(java.lang.StringBuilder buf, Hierarchy<Result> hier, Result result, int depth) Recursively walk through the result tree.

Uses of Result in de.lmu.ifi.dbs.elki.result.outlier

Subinterfaces of Result in de.lmu.ifi.dbs.elki.result.outlier

Modifier and Type	Interface and Description
interface	OutlierScoreMeta Generic meta information about the value range of an outlier score.

Classes in de.lmu.ifi.dbs.elki.result.outlier that implement Result

Modifier and Type	Class and Description
class	BasicOutlierScoreMeta Basic outlier score.
class	InvertedOutlierScoreMeta Class to signal a value-inverted outlier score, i.e. low values are outliers.
class	OrderingFromRelation Ordering obtained from an outlier score.
class	OutlierResult Wrap a typical Outlier result, keeping direct references to the main result parts.
class	ProbabilisticOutlierScore Outlier score that is a probability value in the range 0.0 - 1.0 But the baseline may be different from 0.0!
class	QuotientOutlierScoreMeta Score for outlier values generated by a quotient.

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

Modifier and Type	Method and Description
static java.util.List<OutlierResult>	OutlierResult.getOutlierResults(Result r) Collect all outlier results from a Result

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

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

Modifier and Type	Method and Description
void	TextWriter.output(Database db, Result r, StreamFactory streamOpener, java.util.regex.Pattern filter) Stream output.
private void	TextWriter.writeOtherResult(StreamFactory streamOpener, Result r)

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

Classes in de.lmu.ifi.dbs.elki.visualization that implement Result

Modifier and Type	Class and Description
class	VisualizerContext Map to store context information for the visualizer.

Fields in de.lmu.ifi.dbs.elki.visualization declared as Result

Modifier and Type	Field and Description
private Result	VisualizerContext.baseResult Starting point of the result tree, may be null.

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

Modifier and Type	Method and Description
static <A extends Result,B extends VisualizationItem> void	VisualizationTree.findNewResultVis(VisualizerContext context, java.lang.Object start, java.lang.Class<? super A> type1, java.lang.Class<? super B> type2, java.util.function.BiConsumer<A,B> handler) Process new result combinations of an object type1 (in first hierarchy) having a child of type2 (in second hierarchy).
static <A extends Result,B extends VisualizationItem> void	VisualizationTree.findNewSiblings(VisualizerContext context, java.lang.Object start, java.lang.Class<? super A> type1, java.lang.Class<? super B> type2, java.util.function.BiConsumer<A,B> handler) Process new result combinations of an object type1 (in first hierarchy) and any child of type2 (in second hierarchy) This is a bit painful, because we have two hierarchies with different types: results, and visualizations.

Methods in de.lmu.ifi.dbs.elki.visualization that return Result

Modifier and Type	Method and Description
Result	VisualizerContext.getBaseResult() Starting point for visualization, may be null.

Methods in de.lmu.ifi.dbs.elki.visualization that return types with arguments of type Result

Modifier and Type	Method and Description
static It<Result>	VisualizationTree.findNewResults(VisualizerContext context, java.lang.Object start) Iterate over the primary result tree.

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

Modifier and Type	Method and Description
static java.lang.String	VisualizerParameterizer.getTitle(Database db, Result result) Try to automatically generate a title for this.
VisualizerContext	VisualizerParameterizer.newContext(ResultHierarchy hier, Result start) Make a new visualization context

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

Constructor and Description
VisualizerContext(ResultHierarchy hier, Result start, StyleLibrary stylelib, java.util.Collection<VisualizationProcessor> factories) Constructor.

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

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

Modifier and Type	Method and Description
void	SelectionTableWindow.resultAdded(Result child, Result parent)
void	ResultWindow.resultAdded(Result child, Result parent)
void	SelectionTableWindow.resultChanged(Result current)
void	ResultWindow.resultChanged(Result current)
void	SelectionTableWindow.resultRemoved(Result child, Result parent)
void	ResultWindow.resultRemoved(Result child, Result parent)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.gui.detail

Methods in de.lmu.ifi.dbs.elki.visualization.gui.detail with parameters of type Result

Modifier and Type	Method and Description
void	DetailView.resultAdded(Result child, Result parent)
void	DetailView.resultChanged(Result current)
void	DetailView.resultRemoved(Result child, Result parent)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.gui.overview

Methods in de.lmu.ifi.dbs.elki.visualization.gui.overview with parameters of type Result

Modifier and Type	Method and Description
void	OverviewPlot.resultAdded(Result child, Result parent)
void	OverviewPlot.resultChanged(Result current)
void	OverviewPlot.resultRemoved(Result child, Result parent)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.opticsplot

Classes in de.lmu.ifi.dbs.elki.visualization.opticsplot that implement Result

Modifier and Type	Class and Description
class	OPTICSPlot Class to produce an OPTICS plot image.

Uses of Result in de.lmu.ifi.dbs.elki.visualization.parallel3d

Methods in de.lmu.ifi.dbs.elki.visualization.parallel3d with parameters of type Result

Modifier and Type	Method and Description
void	OpenGL3DParallelCoordinates.processNewResult(ResultHierarchy hier, Result newResult)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.visualizers

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

Modifier and Type	Method and Description
void	AbstractVisualization.resultAdded(Result child, Result parent)
void	AbstractVisualization.resultChanged(Result current)
void	AbstractVisualization.resultRemoved(Result child, Result parent)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.histogram with parameters of type Result

Modifier and Type	Method and Description
void	AbstractHistogramVisualization.resultChanged(Result current)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments with parameters of type Result

Modifier and Type	Method and Description
void	CircleSegmentsVisualizer.Instance.resultChanged(Result current)

Uses of Result in de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.thumbs with parameters of type Result

Modifier and Type	Method and Description
void	ThumbnailVisualization.resultChanged(Result current)

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

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

Modifier and Type	Field and Description
private Result	EvaluationStep.stepresult Result.
private Result	AlgorithmStep.stepresult The algorithm output

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

Modifier and Type	Method and Description
Result	EvaluationStep.getResult() Return the result.
Result	AlgorithmStep.getResult() Get the result.
Result	AlgorithmStep.runAlgorithms(Database database) Run algorithms.

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

Modifier and Type	Method and Description
void	EvaluationStep.Evaluation.resultAdded(Result child, Result parent)
void	EvaluationStep.Evaluation.resultChanged(Result current)
void	EvaluationStep.Evaluation.resultRemoved(Result child, Result parent)
void	EvaluationStep.Evaluation.update(Result r) Update on a particular result.

Uses of Result in tutorial.clustering

Methods in tutorial.clustering that return Result

Modifier and Type	Method and Description
Result	NaiveAgglomerativeHierarchicalClustering1.run(Database db, Relation<O> relation) Run the algorithm
Result	NaiveAgglomerativeHierarchicalClustering2.run(Database db, Relation<O> relation) Run the algorithm
Result	NaiveAgglomerativeHierarchicalClustering3.run(Database db, Relation<O> relation) Run the algorithm

Uses of Result in tutorial.outlier

Methods in tutorial.outlier with parameters of type Result

Modifier and Type	Method and Description
void	SimpleScoreDumper.processNewResult(ResultHierarchy hier, Result newResult)