org.apache.mahout.common.distance

Class WeightedEuclideanDistanceMeasure

java.lang.Object

org.apache.mahout.common.distance.WeightedDistanceMeasure

org.apache.mahout.common.distance.WeightedEuclideanDistanceMeasure

All Implemented Interfaces:

DistanceMeasure, Parametered

public class WeightedEuclideanDistanceMeasure
extends WeightedDistanceMeasure

This class implements a Euclidean distance metric by summing the square root of the squared differences between each coordinate, optionally adding weights.

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.mahout.common.parameters.Parametered

Parametered.ParameteredGeneralizations

Field Summary

Fields inherited from interface org.apache.mahout.common.parameters.Parametered

log

Constructor Summary

Constructors

Constructor and Description
WeightedEuclideanDistanceMeasure()

Method Summary

Methods

Modifier and Type	Method and Description
double	distance(double centroidLengthSquare, Vector centroid, Vector v) Optimized version of distance metric for sparse vectors.
double	distance(Vector p1, Vector p2) Returns the distance metric applied to the arguments

Methods inherited from class org.apache.mahout.common.distance.WeightedDistanceMeasure

configure, createParameters, getParameters, getWeights, setWeights

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

WeightedEuclideanDistanceMeasure

public WeightedEuclideanDistanceMeasure()

Method Detail

distance

public double distance(Vector p1,
              Vector p2)

Description copied from interface: DistanceMeasure

Returns the distance metric applied to the arguments

Parameters:

p1 - a Vector defining a multidimensional point in some feature space

p2 - a Vector defining a multidimensional point in some feature space

Returns:

a scalar doubles of the distance

distance

public double distance(double centroidLengthSquare,
              Vector centroid,
              Vector v)

Description copied from interface: DistanceMeasure

Optimized version of distance metric for sparse vectors. This distance computation requires operations proportional to the number of non-zero elements in the vector instead of the cardinality of the vector.

Parameters:

centroidLengthSquare - Square of the length of centroid

centroid - Centroid vector