Uses of Class
org.openimaj.feature.LongFVComparison

Packages that use LongFVComparison

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

Uses of LongFVComparison in org.openimaj.feature

Methods in org.openimaj.feature that return LongFVComparison

Modifier and Type	Method and Description
static LongFVComparison	LongFVComparison.valueOf(String name) Returns the enum constant of this type with the specified name.
static LongFVComparison[]	LongFVComparison.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 LongFVComparison

Modifier and Type	Method and Description
double	LongFV.compare(LongFV h, LongFVComparison method) Compare this FV to another with the given method.
double	MultidimensionalLongFV.compare(MultidimensionalLongFV h, LongFVComparison method) Compare this FV to another with the given method.

Uses of LongFVComparison in org.openimaj.lsh.functions

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

Modifier and Type	Method and Description
protected LongFVComparison	LongGaussianFactory.fvDistanceFunction()
LongFVComparison	LongHammingFactory.fvDistanceFunction()
protected LongFVComparison	LongCauchyFactory.fvDistanceFunction()
protected abstract LongFVComparison	LongHashFunctionFactory.fvDistanceFunction()
protected LongFVComparison	LongHyperplaneL1Factory.fvDistanceFunction()
protected LongFVComparison	LongHyperplaneCosineFactory.fvDistanceFunction()

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

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

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