Uses of Class
org.openimaj.feature.ByteFVComparison

Packages that use ByteFVComparison

Package	Description
org.openimaj.feature
org.openimaj.lsh.functions
org.openimaj.ml.clustering.assignment.soft

Uses of ByteFVComparison in org.openimaj.feature

Methods in org.openimaj.feature that return ByteFVComparison

Modifier and Type	Method and Description
static ByteFVComparison	ByteFVComparison.valueOf(String name) Returns the enum constant of this type with the specified name.
static ByteFVComparison[]	ByteFVComparison.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.openimaj.feature with parameters of type ByteFVComparison

Modifier and Type	Method and Description
double	ByteFV.compare(ByteFV h, ByteFVComparison method) Compare this FV to another with the given method.
double	MultidimensionalByteFV.compare(MultidimensionalByteFV h, ByteFVComparison method) Compare this FV to another with the given method.

Uses of ByteFVComparison in org.openimaj.lsh.functions

Methods in org.openimaj.lsh.functions that return ByteFVComparison

Modifier and Type	Method and Description
protected ByteFVComparison	ByteHyperplaneCosineFactory.fvDistanceFunction()
protected ByteFVComparison	ByteCauchyFactory.fvDistanceFunction()
protected ByteFVComparison	ByteGaussianFactory.fvDistanceFunction()
protected abstract ByteFVComparison	ByteHashFunctionFactory.fvDistanceFunction()
ByteFVComparison	ByteHammingFactory.fvDistanceFunction()
protected ByteFVComparison	ByteHyperplaneL1Factory.fvDistanceFunction()

Uses of ByteFVComparison in org.openimaj.ml.clustering.assignment.soft

Constructors in org.openimaj.ml.clustering.assignment.soft with parameters of type ByteFVComparison

Constructor and Description
ByteKNNAssigner(byte[][] data, ByteFVComparison comparison, int numNeighbours) Construct the assigner using the given cluster data and distance function.
ByteKNNAssigner(CentroidsProvider<byte[]> provider, ByteFVComparison comparison, int numNeighbours) Construct the assigner using the given cluster data and distance function.