Uses of Interface
org.openimaj.ml.clustering.Clusters

Packages that use Clusters

Package	Description
org.openimaj.ml.clustering
org.openimaj.ml.clustering.dbscan
org.openimaj.ml.clustering.kdtree
org.openimaj.ml.clustering.kmeans	K-Means in OpenIMAJ is designed to be both extremely fast and flexible.
org.openimaj.ml.clustering.rac
org.openimaj.ml.clustering.rforest
org.openimaj.ml.clustering.spectral

Uses of Clusters in org.openimaj.ml.clustering

Subinterfaces of Clusters in org.openimaj.ml.clustering

Modifier and Type	Interface and Description
interface	SpatialClusters<DATATYPE> Interface to describe objects that are the result of the clustering performed by a SpatialClusterer.

Classes in org.openimaj.ml.clustering that implement Clusters

Modifier and Type	Class and Description
class	ByteCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.
class	DoubleCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.
class	FeatureVectorCentroidsResult<T extends FeatureVector> The result of a SpatialClusterer that just produces a flat set of centroids in the form of FeatureVectors.
class	FloatCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.
class	IndexClusters Class to describe objects that are the result of the clustering where the training data is implicitly clustered
class	IntCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.
class	LongCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.
class	ShortCentroidsResult The result of a SpatialClusterer that just produces a flat set of centroids.

Uses of Clusters in org.openimaj.ml.clustering.dbscan

Classes in org.openimaj.ml.clustering.dbscan that implement Clusters

Modifier and Type	Class and Description
class	DBSCANClusters
class	DoubleDBSCANClusters DBSCANClusters which also holds the original data

Uses of Clusters in org.openimaj.ml.clustering.kdtree

Classes in org.openimaj.ml.clustering.kdtree that implement Clusters

Modifier and Type	Class and Description
class	KDTreeClusters

Uses of Clusters in org.openimaj.ml.clustering.kmeans

Classes in org.openimaj.ml.clustering.kmeans that implement Clusters

Modifier and Type	Class and Description
static class	ByteKMeans.Result Result object for ByteKMeans, extending ByteCentroidsResult and ByteNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
static class	DoubleKMeans.Result Result object for DoubleKMeans, extending DoubleCentroidsResult and DoubleNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
static class	FeatureVectorKMeans.Result<T extends FeatureVector> Result object for FeatureVectorKMeans, extending FeatureVectorCentroidsResult and ObjectNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
static class	FloatKMeans.Result Result object for FloatKMeans, extending FloatCentroidsResult and FloatNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
class	HierarchicalByteKMeansResult The result of a HierarchicalByteKMeans clustering operation.
class	HierarchicalDoubleKMeansResult The result of a HierarchicalDoubleKMeans clustering operation.
class	HierarchicalFloatKMeansResult The result of a HierarchicalFloatKMeans clustering operation.
class	HierarchicalIntKMeansResult The result of a HierarchicalIntKMeans clustering operation.
class	HierarchicalLongKMeansResult The result of a HierarchicalLongKMeans clustering operation.
class	HierarchicalShortKMeansResult The result of a HierarchicalShortKMeans clustering operation.
static class	IntKMeans.Result Result object for IntKMeans, extending IntCentroidsResult and IntNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
static class	LongKMeans.Result Result object for LongKMeans, extending LongCentroidsResult and LongNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
static class	ShortKMeans.Result Result object for ShortKMeans, extending ShortCentroidsResult and ShortNearestNeighboursProvider, as well as giving access to state information from the operation of the K-Means algorithm (i.e.
class	SphericalKMeansResult The result of a SpatialClusterer that just produces a flat set of centroids.

Uses of Clusters in org.openimaj.ml.clustering.rac

Classes in org.openimaj.ml.clustering.rac that implement Clusters

Modifier and Type	Class and Description
class	ClusterLimitedIntRAC Similar to IntRAC but explicitly specify the limit the number of clusters.
class	IntRAC An implementation of the RAC algorithm proposed by Ramanan and Niranjan.

Uses of Clusters in org.openimaj.ml.clustering.rforest

Classes in org.openimaj.ml.clustering.rforest that implement Clusters

Modifier and Type	Class and Description
class	IntRandomForest An implementation of the RandomForest clustering algorithm proposed by Jurie et al.

Uses of Clusters in org.openimaj.ml.clustering.spectral

Classes in org.openimaj.ml.clustering.spectral that implement Clusters

Modifier and Type	Class and Description
class	SpectralIndexedClusters IndexClusters which also hold the eigenvector/value pairs which created them