Uses of Interface
weka.core.DistanceFunction

Packages that use DistanceFunction

Package	Description
weka.clusterers
weka.core
weka.core.neighboursearch
weka.core.neighboursearch.balltrees

Uses of DistanceFunction in weka.clusterers

Methods in weka.clusterers that return DistanceFunction

Modifier and Type	Method	Description
DistanceFunction	HierarchicalClusterer.getDistanceFunction()
DistanceFunction	SimpleKMeans.getDistanceFunction()	returns the distance function currently in use.

Methods in weka.clusterers with parameters of type DistanceFunction

Modifier and Type	Method	Description
void	HierarchicalClusterer.setDistanceFunction(DistanceFunction distanceFunction)
void	SimpleKMeans.setDistanceFunction(DistanceFunction df)	sets the distance function to use for instance comparison.

Uses of DistanceFunction in weka.core

Classes in weka.core that implement DistanceFunction

Modifier and Type	Class	Description
class	ChebyshevDistance	Implements the Chebyshev distance.
class	EuclideanDistance	Implementing Euclidean distance (or similarity) function. One object defines not one distance but the data model in which the distances between objects of that data model can be computed. Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low. For more information, see: Wikipedia.
class	FilteredDistance	Applies the given filter before calling the given distance function.
class	ManhattanDistance	Implements the Manhattan distance (or Taxicab geometry).
class	MinkowskiDistance	Implementing Minkowski distance (or similarity) function. One object defines not one distance but the data model in which the distances between objects of that data model can be computed. Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low. For more information, see: Wikipedia.
class	NormalizableDistance	Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.

Methods in weka.core that return DistanceFunction

Modifier and Type	Method	Description
DistanceFunction	FilteredDistance.getDistance()	Gets the distance used.

Methods in weka.core with parameters of type DistanceFunction

Modifier and Type	Method	Description
void	FilteredDistance.setDistance(DistanceFunction distance)	Sets the distance

Uses of DistanceFunction in weka.core.neighboursearch

Methods in weka.core.neighboursearch that return DistanceFunction

Modifier and Type	Method	Description
DistanceFunction	KDTree.getDistanceFunction()	returns the distance function currently in use.
DistanceFunction	NearestNeighbourSearch.getDistanceFunction()	returns the distance function currently in use.

Methods in weka.core.neighboursearch with parameters of type DistanceFunction

Modifier and Type	Method	Description
void	CoverTree.setDistanceFunction(DistanceFunction df)	Sets the distance function to use for nearest neighbour search.
void	KDTree.setDistanceFunction(DistanceFunction df)	sets the distance function to use for nearest neighbour search.
void	NearestNeighbourSearch.setDistanceFunction(DistanceFunction df)	sets the distance function to use for nearest neighbour search.

Uses of DistanceFunction in weka.core.neighboursearch.balltrees

Methods in weka.core.neighboursearch.balltrees with parameters of type DistanceFunction

Modifier and Type	Method	Description
static double	BallNode.calcRadius(int[] instList, Instances insts, Instance pivot, DistanceFunction distanceFunction)	Calculates the radius of node.
static double	BallNode.calcRadius(int start, int end, int[] instList, Instances insts, Instance pivot, DistanceFunction distanceFunction)	Calculates the radius of a node.
static double	BallNode.calcRadius(BallNode child1, BallNode child2, Instance pivot, DistanceFunction distanceFunction)	Calculates the radius of a node based on its two child nodes (if merging two nodes).