Uses of Interface weka.core.DistanceFunction (weka-dev 3.9.7 API)

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).