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.
|
Modifier and Type | Class and Description |
---|---|
static class |
KNNDistancesSampler.KNNDistanceOrderResult
Curve result for a list containing the knn distances.
|
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.
|
Modifier and Type | Method and Description |
---|---|
Result |
ValidateApproximativeKNNIndex.run(Database database,
Relation<O> relation)
Run the algorithm.
|
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
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractClassifier<O,R extends Result>
Abstract base class for algorithms.
|
Modifier and Type | Method and Description |
---|---|
Result |
KNNClassifier.run(Database database)
Deprecated.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractHDBSCAN<O,R extends Result>
Abstract base class for HDBSCAN variations.
|
Modifier and Type | Class and Description |
---|---|
class |
PointerDensityHierarchyRepresentationResult
Extended pointer representation useful for HDBSCAN.
|
class |
PointerHierarchyRepresentationResult
The pointer representation of a hierarchical clustering.
|
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.
|
Modifier and Type | Class and Description |
---|---|
static class |
DiSH.DiSHClusterOrder
DiSH cluster order.
|
Modifier and Type | Class and Description |
---|---|
static class |
RepresentativeUncertainClustering.RepresentativenessEvaluation
Representativeness evaluation result.
|
Modifier and Type | Method and Description |
---|---|
protected Clustering<?> |
RepresentativeUncertainClustering.runClusteringAlgorithm(ResultHierarchy hierarchy,
Result parent,
DBIDs ids,
DataStore<DoubleVector> store,
int dim,
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,
String title)
Run a clustering algorithm on a single instance.
|
Modifier and Type | Method and Description |
---|---|
private OutlierResult |
RescaleMetaOutlierAlgorithm.getOutlierResult(ResultHierarchy hier,
Result result)
Find an OutlierResult to work with.
|
Modifier and Type | Interface and Description |
---|---|
interface |
NeighborSetPredicate
Predicate to obtain the neighbors of a reference object as set.
|
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.
|
Modifier and Type | Class and Description |
---|---|
static class |
EvaluateRetrievalPerformance.RetrievalPerformanceResult
Result object for MAP scores.
|
Modifier and Type | Method and Description |
---|---|
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 |
DistanceQuantileSampler.run(Database database,
Relation<O> rel) |
Result |
RangeQuerySelectivity.run(Database database,
Relation<V> relation) |
Modifier and Type | Field and Description |
---|---|
private Result |
JSONWebServer.baseResult
Starting point.
|
Modifier and Type | Method and Description |
---|---|
void |
JSONResultHandler.processNewResult(ResultHierarchy hier,
Result newResult) |
Constructor and Description |
---|
JSONWebServer(int port,
ResultHierarchy hier,
Result baseResult)
Constructor.
|
Modifier and Type | Class and Description |
---|---|
class |
Clustering<M extends Model>
Result class for clusterings.
|
Modifier and Type | Class and Description |
---|---|
class |
CorrelationAnalysisSolution<V extends NumberVector>
A solution of correlation analysis is a matrix of equations describing the
dependencies.
|
Modifier and Type | Interface and Description |
---|---|
interface |
Database
Database specifies the requirements for any database implementation.
|
interface |
UpdatableDatabase
Database API with updates.
|
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.
|
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. |
Modifier and Type | Interface and Description |
---|---|
interface |
DataStore<T>
Generic storage interface for objects indexed by
DBID . |
interface |
DBIDDataStore
DBID-valued data store (avoids boxing/unboxing).
|
interface |
DoubleDataStore
Double-valued data store (avoids boxing/unboxing).
|
interface |
IntegerDataStore
Integer-valued data store (avoids boxing/unboxing).
|
interface |
WritableDataStore<T>
Writable data store.
|
interface |
WritableDBIDDataStore
Data store specialized for doubles.
|
interface |
WritableDoubleDataStore
Data store specialized for doubles.
|
interface |
WritableIntegerDataStore
Data store specialized for doubles.
|
Modifier and Type | Class and Description |
---|---|
class |
ArrayDBIDStore
A class to answer representation queries using the stored Array.
|
class |
ArrayDoubleStore
A class to answer representation queries using the stored Array.
|
class |
ArrayIntegerStore
A class to answer representation queries using the stored Array.
|
protected class |
ArrayRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
ArrayStore<T>
A class to answer representation queries using the stored Array.
|
class |
MapIntegerDBIDDBIDStore
Writable data store for double values.
|
class |
MapIntegerDBIDDoubleStore
Writable data store for double values.
|
class |
MapIntegerDBIDIntegerStore
Writable data store for double values.
|
protected class |
MapIntegerDBIDRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
MapIntegerDBIDStore<T>
A class to answer representation queries using a map.
|
protected class |
MapRecordStore.StorageAccessor<T>
Access a single record in the given data.
|
class |
MapStore<T>
A class to answer representation queries using a map.
|
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.
|
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.
|
Modifier and Type | Method and Description |
---|---|
protected void |
AutomaticEvaluation.autoEvaluateClusterings(ResultHierarchy hier,
Result newResult) |
protected void |
AutomaticEvaluation.autoEvaluateOutliers(ResultHierarchy hier,
Result newResult) |
void |
NoAutomaticEvaluation.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
AutomaticEvaluation.processNewResult(ResultHierarchy hier,
Result newResult) |
Modifier and Type | Class and Description |
---|---|
class |
ConfusionMatrixEvaluationResult
Provides the prediction performance measures for a classifier based on the
confusion matrix.
|
Modifier and Type | Class and Description |
---|---|
static class |
EvaluateClustering.ScoreResult
Result object for outlier score judgements.
|
Modifier and Type | Method and Description |
---|---|
void |
LogClusterSizes.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateClustering.processNewResult(ResultHierarchy hier,
Result newResult) |
Modifier and Type | Method and Description |
---|---|
void |
SimplifiedHierarchyExtractionEvaluator.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
HDBSCANHierarchyExtractionEvaluator.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
ExtractFlatClusteringFromHierarchyEvaluator.processNewResult(ResultHierarchy hier,
Result newResult) |
Modifier and Type | Method and Description |
---|---|
void |
EvaluateVarianceRatioCriteria.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateSquaredErrors.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateSimplifiedSilhouette.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateSilhouette.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluatePBMIndex.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateDaviesBouldin.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateConcordantPairs.processNewResult(ResultHierarchy hier,
Result result) |
void |
EvaluateCIndex.processNewResult(ResultHierarchy hier,
Result result) |
Modifier and Type | Class and Description |
---|---|
class |
Segments
Creates segments of two or more clusterings.
|
Modifier and Type | Method and Description |
---|---|
void |
ClusterPairSegmentAnalysis.processNewResult(ResultHierarchy hier,
Result result)
Perform clusterings evaluation
|
Modifier and Type | Method and Description |
---|---|
void |
ComputeOutlierHistogram.processNewResult(ResultHierarchy hier,
Result newResult) |
Modifier and Type | Class and Description |
---|---|
class |
IndexStatistics.IndexMetaResult
Result class.
|
Modifier and Type | Method and Description |
---|---|
void |
IndexStatistics.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
IndexPurity.processNewResult(ResultHierarchy hier,
Result newResult) |
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.
|
Modifier and Type | Method and Description |
---|---|
void |
OutlierThresholdClustering.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
OutlierSmROCCurve.processNewResult(ResultHierarchy hier,
Result result) |
void |
OutlierRankingEvaluation.processNewResult(ResultHierarchy hier,
Result result) |
void |
OutlierROCCurve.processNewResult(ResultHierarchy hier,
Result result) |
void |
OutlierPrecisionRecallCurve.processNewResult(ResultHierarchy hier,
Result result) |
void |
OutlierPrecisionAtKCurve.processNewResult(ResultHierarchy hier,
Result result) |
void |
JudgeOutlierScores.processNewResult(ResultHierarchy hier,
Result result) |
Modifier and Type | Class and Description |
---|---|
static class |
ComputeSimilarityMatrixImage.SimilarityMatrix
Similarity matrix image.
|
Modifier and Type | Method and Description |
---|---|
void |
ComputeSimilarityMatrixImage.processNewResult(ResultHierarchy hier,
Result result) |
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 kNN queries.
|
interface |
RKNNIndex<O>
Index with support for kNN queries.
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
PrecomputedDistanceMatrix<O>
Distance matrix, for precomputing similarity for a small data set.
|
Modifier and Type | Class and Description |
---|---|
class |
InMemoryIDistanceIndex<O>
In-memory iDistance index, a metric indexing method using a reference point
embedding.
|
Modifier and Type | Class and Description |
---|---|
class |
InMemoryInvertedIndex<V extends NumberVector>
Simple index using inverted lists.
|
Modifier and Type | Class and Description |
---|---|
class |
InMemoryLSHIndex.Instance
Instance of a LSH index for a single relation.
|
Modifier and Type | Interface and Description |
---|---|
interface |
LocalProjectionIndex<V extends NumberVector,P extends ProjectionResult>
Abstract index interface for local projections
|
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.
|
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 |
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.
|
Modifier and Type | Interface and Description |
---|---|
interface |
FilteredLocalPCAIndex<NV extends NumberVector>
Interface for an index providing local PCA results.
|
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.
|
Modifier and Type | Interface and Description |
---|---|
interface |
PreferenceVectorIndex<NV extends NumberVector>
Interface for an index providing preference vectors.
|
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.
|
Modifier and Type | Interface and Description |
---|---|
interface |
SharedNearestNeighborIndex<O>
Interface for an index providing nearest neighbor sets.
|
Modifier and Type | Class and Description |
---|---|
class |
SharedNearestNeighborPreprocessor<O>
A preprocessor for annotation of the ids of nearest neighbors to each
database object.
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
IndexTree<N extends Node<E>,E extends Entry>
Abstract super class for all tree based index classes.
|
Modifier and Type | Class and Description |
---|---|
class |
MetricalIndexTree<O,N extends Node<E>,E extends Entry>
Abstract super class for all metrical index classes.
|
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).
|
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.
|
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.
|
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.
|
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.
|
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
|
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.
|
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.
|
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.
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends AbstractRTreeSettings>
Abstract superclass for index structures based on a R*-Tree.
|
class |
NonFlatRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends AbstractRTreeSettings>
Abstract superclass for all non-flat R*-Tree variants.
|
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.
|
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.
|
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.
|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
PartialVAFile<V extends NumberVector>
PartialVAFile.
|
class |
VAFile<V extends NumberVector>
Vector-approximation file (VAFile)
Reference:
Weber, R. and Blott, S.
|
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.Curve s, meant for chart
generation. |
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.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractHierarchicalResult
Abstract class for a result object with hierarchy
|
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 Apriori Algorithm.
|
class |
HistogramResult<O>
Histogram result.
|
class |
OrderingFromDataStore<T extends 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.
|
Modifier and Type | Method and Description |
---|---|
static <C extends Result> |
ResultUtil.filterResults(ResultHierarchy hier,
Class<? super C> restrictionClass)
Return only results of the given restriction class
|
static <C extends Result> |
ResultUtil.filterResults(ResultHierarchy hier,
Result r,
Class<? super C> restrictionClass)
Return only results of the given restriction class
|
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 void |
ResultUtil.ensureClusteringResult(Database db,
Result result)
Ensure that the result contains at least one Clustering.
|
static <C extends Result> |
ResultUtil.filterResults(ResultHierarchy hier,
Result r,
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,
String name,
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 List<Clustering<? extends Model>> |
ResultUtil.getClusteringResults(Result r)
Collect all clustering results from a Result
|
static List<CollectionResult<?>> |
ResultUtil.getCollectionResults(Result r)
Collect all collection results from a Result
|
static List<IterableResult<?>> |
ResultUtil.getIterableResults(Result r)
Return all Iterable results
|
static List<OrderingResult> |
ResultUtil.getOrderingResults(Result r)
Collect all ordering results from a Result
|
static List<OutlierResult> |
ResultUtil.getOutlierResults(Result r)
Collect all outlier results from a Result
|
static List<Relation<?>> |
ResultUtil.getRelations(Result r)
Collect all Annotation results from a Result
|
static List<SettingsResult> |
ResultUtil.getSettingsResults(Result r)
Collect all settings results from a Result
|
void |
ResultWriter.processNewResult(ResultHierarchy hier,
Result result) |
void |
ResultProcessor.processNewResult(ResultHierarchy hier,
Result newResult)
Process a result.
|
void |
LogResultStructureResultHandler.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
KMLOutputHandler.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
DiscardResultHandler.processNewResult(ResultHierarchy hier,
Result newResult) |
void |
ClusteringVectorDumper.processNewResult(ResultHierarchy hier,
Result newResult) |
private void |
LogResultStructureResultHandler.recursiveLogResult(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.
|
Modifier and Type | Method and Description |
---|---|
private void |
LogResultStructureResultHandler.recursiveLogResult(StringBuilder buf,
Hierarchy<Result> hier,
Result result,
int depth)
Recursively walk through the result tree.
|
Modifier and Type | Interface and Description |
---|---|
interface |
OutlierScoreMeta
Generic meta information about the value range of an outlier score.
|
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.
|
Modifier and Type | Method and Description |
---|---|
void |
TextWriter.output(Database db,
Result r,
StreamFactory streamOpener,
Pattern filter)
Stream output.
|
private void |
TextWriter.writeOtherResult(StreamFactory streamOpener,
Result r) |
Modifier and Type | Class and Description |
---|---|
class |
VisualizerContext
Map to store context information for the visualizer.
|
Modifier and Type | Field and Description |
---|---|
private Result |
VisualizerContext.baseResult
Starting point of the result tree, may be
null . |
(package private) Result |
ExportVisualizations.baseResult
Base result
|
Modifier and Type | Method and Description |
---|---|
static <O extends Result> |
VisualizationTree.filterResults(VisualizerContext context,
Object start,
Class<? super O> clazz)
Filtered iteration over the primary result tree.
|
static <A extends Result,B extends VisualizationItem> |
VisualizationTree.findNewResultVis(VisualizerContext context,
Object start,
Class<? super A> type1,
Class<? super B> type2,
VisualizationTree.Handler2<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> |
VisualizationTree.findNewSiblings(VisualizerContext context,
Object start,
Class<? super A> type1,
Class<? super B> type2,
VisualizationTree.Handler2<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.
|
Modifier and Type | Method and Description |
---|---|
Result |
VisualizerContext.getBaseResult()
Starting point for visualization, may be
null . |
Modifier and Type | Method and Description |
---|---|
static 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
|
void |
ExportVisualizations.processNewResult(ResultHierarchy hier,
Result newResult) |
Constructor and Description |
---|
VisualizerContext(ResultHierarchy hier,
Result start,
Relation<?> relation,
StyleLibrary stylelib,
Collection<VisualizationProcessor> factories)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
void |
ResultVisualizer.processNewResult(ResultHierarchy hier,
Result result) |
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) |
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) |
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) |
Modifier and Type | Class and Description |
---|---|
class |
OPTICSPlot
Class to produce an OPTICS plot image.
|
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) |
Modifier and Type | Method and Description |
---|---|
void |
AbstractHistogramVisualization.resultChanged(Result current) |
Modifier and Type | Method and Description |
---|---|
protected static Clustering<OPTICSModel> |
OPTICSClusterVisualization.findOPTICSClustering(VisualizerContext context,
Result start)
Find the first OPTICS clustering child of a result.
|
Modifier and Type | Method and Description |
---|---|
void |
CircleSegmentsVisualizer.Instance.resultChanged(Result current) |
Modifier and Type | Method and Description |
---|---|
void |
ThumbnailVisualization.resultChanged(Result current) |
Modifier and Type | Field and Description |
---|---|
private Result |
EvaluationStep.stepresult
Result.
|
private Result |
AlgorithmStep.stepresult
The algorithm output
|
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.
|
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.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.