Uses of Class
org.openimaj.ml.clustering.kmeans.KMeansConfiguration

Packages that use KMeansConfiguration

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

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

Methods in org.openimaj.ml.clustering.kmeans that return KMeansConfiguration

Modifier and Type	Method and Description
KMeansConfiguration<NN,DATA>	KMeansConfiguration.clone()
KMeansConfiguration<FloatNearestNeighbours,float[]>	FloatKMeans.getConfiguration() Get the configuration
KMeansConfiguration<ShortNearestNeighbours,short[]>	ShortKMeans.getConfiguration() Get the configuration
KMeansConfiguration<IntNearestNeighbours,int[]>	IntKMeans.getConfiguration() Get the configuration
KMeansConfiguration<ByteNearestNeighbours,byte[]>	ByteKMeans.getConfiguration() Get the configuration
KMeansConfiguration<LongNearestNeighbours,long[]>	LongKMeans.getConfiguration() Get the configuration
KMeansConfiguration<ObjectNearestNeighbours<T>,T>	FeatureVectorKMeans.getConfiguration() Get the configuration
KMeansConfiguration<DoubleNearestNeighbours,double[]>	DoubleKMeans.getConfiguration() Get the configuration

Methods in org.openimaj.ml.clustering.kmeans with parameters of type KMeansConfiguration

Modifier and Type	Method and Description
void	ByteKMeans.setConfiguration(KMeansConfiguration<ByteNearestNeighbours,byte[]> conf) Set the configuration
void	DoubleKMeans.setConfiguration(KMeansConfiguration<DoubleNearestNeighbours,double[]> conf) Set the configuration
void	FloatKMeans.setConfiguration(KMeansConfiguration<FloatNearestNeighbours,float[]> conf) Set the configuration
void	IntKMeans.setConfiguration(KMeansConfiguration<IntNearestNeighbours,int[]> conf) Set the configuration
void	LongKMeans.setConfiguration(KMeansConfiguration<LongNearestNeighbours,long[]> conf) Set the configuration
void	FeatureVectorKMeans.setConfiguration(KMeansConfiguration<ObjectNearestNeighbours<T>,T> conf) Set the configuration
void	ShortKMeans.setConfiguration(KMeansConfiguration<ShortNearestNeighbours,short[]> conf) Set the configuration

Constructors in org.openimaj.ml.clustering.kmeans with parameters of type KMeansConfiguration

Constructor and Description
ByteKMeans(KMeansConfiguration<ByteNearestNeighbours,byte[]> conf) Construct the clusterer with the the given configuration.
DoubleKMeans(KMeansConfiguration<DoubleNearestNeighbours,double[]> conf) Construct the clusterer with the the given configuration.
FeatureVectorKMeans(KMeansConfiguration<ObjectNearestNeighbours<T>,T> conf) Construct the clusterer with the the given configuration.
FloatKMeans(KMeansConfiguration<FloatNearestNeighbours,float[]> conf) Construct the clusterer with the the given configuration.
HierarchicalByteKMeans(KMeansConfiguration<ByteNearestNeighbours,byte[]> config, int M, int K, int depth) Construct a new HierarchicalByteKMeans with the given parameters.
HierarchicalDoubleKMeans(KMeansConfiguration<DoubleNearestNeighbours,double[]> config, int M, int K, int depth) Construct a new HierarchicalDoubleKMeans with the given parameters.
HierarchicalFloatKMeans(KMeansConfiguration<FloatNearestNeighbours,float[]> config, int M, int K, int depth) Construct a new HierarchicalFloatKMeans with the given parameters.
HierarchicalIntKMeans(KMeansConfiguration<IntNearestNeighbours,int[]> config, int M, int K, int depth) Construct a new HierarchicalIntKMeans with the given parameters.
HierarchicalLongKMeans(KMeansConfiguration<LongNearestNeighbours,long[]> config, int M, int K, int depth) Construct a new HierarchicalLongKMeans with the given parameters.
HierarchicalShortKMeans(KMeansConfiguration<ShortNearestNeighbours,short[]> config, int M, int K, int depth) Construct a new HierarchicalShortKMeans with the given parameters.
IntKMeans(KMeansConfiguration<IntNearestNeighbours,int[]> conf) Construct the clusterer with the the given configuration.
LongKMeans(KMeansConfiguration<LongNearestNeighbours,long[]> conf) Construct the clusterer with the the given configuration.
ShortKMeans(KMeansConfiguration<ShortNearestNeighbours,short[]> conf) Construct the clusterer with the the given configuration.