Uses of Package
org.openimaj.ml.clustering.kmeans

Packages that use org.openimaj.ml.clustering.kmeans

Package	Description
org.openimaj.hadoop.tools.fastkmeans
org.openimaj.image.segmentation
org.openimaj.ml.clustering.assignment.hard
org.openimaj.ml.clustering.assignment.soft
org.openimaj.ml.clustering.kmeans	K-Means in OpenIMAJ is designed to be both extremely fast and flexible.
org.openimaj.tools.clusterquantiser.fastkmeans

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.hadoop.tools.fastkmeans

Class and Description
ByteKMeansInit Initialisation for K-Means clustering.

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.image.segmentation

Class and Description
FloatKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.ml.clustering.assignment.hard

Class and Description
HierarchicalByteKMeansResult The result of a HierarchicalByteKMeans clustering operation.
HierarchicalDoubleKMeansResult The result of a HierarchicalDoubleKMeans clustering operation.
HierarchicalFloatKMeansResult The result of a HierarchicalFloatKMeans clustering operation.
HierarchicalIntKMeansResult The result of a HierarchicalIntKMeans clustering operation.
HierarchicalLongKMeansResult The result of a HierarchicalLongKMeans clustering operation.
HierarchicalShortKMeansResult The result of a HierarchicalShortKMeans clustering operation.

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.ml.clustering.assignment.soft

Class and Description
HierarchicalByteKMeansResult The result of a HierarchicalByteKMeans clustering operation.
HierarchicalDoubleKMeansResult The result of a HierarchicalDoubleKMeans clustering operation.
HierarchicalFloatKMeansResult The result of a HierarchicalFloatKMeans clustering operation.
HierarchicalIntKMeansResult The result of a HierarchicalIntKMeans clustering operation.
HierarchicalLongKMeansResult The result of a HierarchicalLongKMeans clustering operation.
HierarchicalShortKMeansResult The result of a HierarchicalShortKMeans clustering operation.

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.ml.clustering.kmeans

Class and Description
ByteKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
ByteKMeansInit Initialisation for K-Means clustering.
DoubleKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
DoubleKMeansInit Initialisation for K-Means clustering.
FeatureVectorKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
FeatureVectorKMeans.Result 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.
FeatureVectorKMeansInit Initialisation for K-Means clustering.
FloatKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
FloatKMeansInit Initialisation for K-Means clustering.
HierarchicalByteKMeansResult The result of a HierarchicalByteKMeans clustering operation.
HierarchicalByteKMeansResult.Node HierarchicalByteKMeans tree node The number of children is not bigger than the HierarchicalByteKMeans K parameter
HierarchicalDoubleKMeansResult The result of a HierarchicalDoubleKMeans clustering operation.
HierarchicalDoubleKMeansResult.Node HierarchicalDoubleKMeans tree node The number of children is not bigger than the HierarchicalDoubleKMeans K parameter
HierarchicalFloatKMeansResult The result of a HierarchicalFloatKMeans clustering operation.
HierarchicalFloatKMeansResult.Node HierarchicalFloatKMeans tree node The number of children is not bigger than the HierarchicalFloatKMeans K parameter
HierarchicalIntKMeansResult The result of a HierarchicalIntKMeans clustering operation.
HierarchicalIntKMeansResult.Node HierarchicalIntKMeans tree node The number of children is not bigger than the HierarchicalIntKMeans K parameter
HierarchicalLongKMeansResult The result of a HierarchicalLongKMeans clustering operation.
HierarchicalLongKMeansResult.Node HierarchicalLongKMeans tree node The number of children is not bigger than the HierarchicalLongKMeans K parameter
HierarchicalShortKMeansResult The result of a HierarchicalShortKMeans clustering operation.
HierarchicalShortKMeansResult.Node HierarchicalShortKMeans tree node The number of children is not bigger than the HierarchicalShortKMeans K parameter
IntKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
IntKMeansInit Initialisation for K-Means clustering.
KMeansConfiguration Configuration for the K-Means algorithm.
LongKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
LongKMeansInit Initialisation for K-Means clustering.
ShortKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.
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.
ShortKMeansInit Initialisation for K-Means clustering.
SphericalKMeans.IterationResult Object storing the result of the previous iteration of spherical kmeans.
SphericalKMeansResult The result of a SpatialClusterer that just produces a flat set of centroids.

Classes in org.openimaj.ml.clustering.kmeans used by org.openimaj.tools.clusterquantiser.fastkmeans

Class and Description
ByteKMeans Fast, parallel implementation of the K-Means algorithm with support for bigger-than-memory data.