org.openimaj.ml.clustering

Interface DataClusterer<DATA,CLUSTER extends IndexClusters>

Type Parameters:

DATA - the data which can be clustered

CLUSTER -

All Superinterfaces:

Clusterer<DATA>

All Known Subinterfaces:

DistanceClusterer<CLUSTERS>, MultiviewSimilarityClusterer<CLUSTERS>, SimilarityClusterer<CLUSTERS>, SparseMatrixClusterer<CLUSTERS>

All Known Implementing Classes:

CachedDoubleSpectralClustering, ContectedComponentSimilarityClusterer, DistanceDBSCAN, DoubleMultiviewSpectralClustering, DoubleNNDBSCAN, DoubleSpectralClustering, IncrementalLifetimeSparseClusterer, IncrementalSparseClusterer, PreparedSpectralClustering, RandomClusterer, SimilarityDBSCAN, SparseMatrixDBSCAN

public interface DataClusterer<DATA,CLUSTER extends IndexClusters>
extends Clusterer<DATA>

Clusterers can extract clusters from data types and return the data in a clustered form

Author:

Sina Samangooei (ss@ecs.soton.ac.uk)

Method Summary

Modifier and Type	Method and Description
CLUSTER	cluster(DATA data)

Methods inherited from interface org.openimaj.experiment.evaluation.cluster.processor.Clusterer

performClustering

Method Detail

cluster

CLUSTER cluster(DATA data)

Parameters:

data - the data to be clustered

Returns:

the clusters produced