Uses of Class
de.lmu.ifi.dbs.elki.result.ClusterOrderResult

Packages that use ClusterOrderResult

de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation 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.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d	Visualizers based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj	Visualizers that do not use a particular projection.

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

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

protected ClusterOrderResult<D>	DeLiClu.runInTime(Database<O> database) Performs the DeLiClu algorithm on the given database.
protected ClusterOrderResult<D>	OPTICS.runInTime(Database<O> database) Performs the OPTICS algorithm on the given database.

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

protected void

OPTICS.expandClusterOrder(ClusterOrderResult<D> clusterOrder, Database<O> database, Integer objectID, FiniteProgress progress) OPTICS-function expandClusterOrder.

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

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

protected ClusterOrderResult<PCACorrelationDistance>

HiCO.runInTime(Database<V> database)

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return ClusterOrderResult

protected ClusterOrderResult<PreferenceVectorBasedCorrelationDistance>

HiSC.runInTime(Database<V> database)

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

private Clustering<SubspaceModel<V>>	DiSH.computeClusters(Database<V> database, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance> clusterOrder) Computes the hierarchical clusters according to the cluster order.
private Map<BitSet,List<Pair<BitSet,DatabaseObjectGroupCollection<List<Integer>>>>>	DiSH.extractClusters(Database<V> database, DiSHDistanceFunction<V,DiSHPreprocessor<V>> distanceFunction, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance> clusterOrder) Extracts the clusters from the cluster order.

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

Fields in de.lmu.ifi.dbs.elki.visualization.opticsplot declared as ClusterOrderResult

(package private) ClusterOrderResult<D>

OPTICSPlot.co The result to plot

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

OPTICSPlot(ClusterOrderResult<D> co, OPTICSColorAdapter colors, OPTICSDistanceAdapter<D> distanceAdapter)
Constructor.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d

Fields in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d declared as ClusterOrderResult

private ClusterOrderResult<?>

ClusterOrderVisualizer.result The result we visualize

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d with parameters of type ClusterOrderResult

void	ClusterOrderVisualizer.init(VisualizerContext context, ClusterOrderResult<?> result) Initialize the visualizer.

Uses of ClusterOrderResult in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj

Fields in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj declared as ClusterOrderResult

(package private) ClusterOrderResult<D>

OPTICSPlotVisualizer.co Curve to visualize

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

static <D extends Distance<?>> boolean	OPTICSPlotVisualizer.canPlot(ClusterOrderResult<D> co) Test whether we have an adapter for this cluster orders distance.
private static <D extends Distance<?>> OPTICSDistanceAdapter<D>	OPTICSPlotVisualizer.getAdapterForDistance(ClusterOrderResult<D> co) Try to find a distance adapter.
void	OPTICSPlotVisualizer.init(VisualizerContext context, ClusterOrderResult<D> co) Initialization.