org.apache.mahout.common.distance
Class WeightedEuclideanDistanceMeasure

java.lang.Object
  extended by org.apache.mahout.common.distance.WeightedDistanceMeasure
      extended by 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
WeightedEuclideanDistanceMeasure()
           
 
Method Summary
 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


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