org.apache.mahout.common.distance
Interface DistanceMeasure

All Superinterfaces:
Parametered
All Known Implementing Classes:
ChebyshevDistanceMeasure, CosineDistanceMeasure, EuclideanDistanceMeasure, MahalanobisDistanceMeasure, ManhattanDistanceMeasure, MinkowskiDistanceMeasure, SquaredEuclideanDistanceMeasure, TanimotoDistanceMeasure, WeightedDistanceMeasure, WeightedEuclideanDistanceMeasure, WeightedManhattanDistanceMeasure

public interface DistanceMeasure
extends Parametered

This interface is used for objects which can determine a distance metric between two points


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
 
Method Summary
 double distance(double centroidLengthSquare, Vector centroid, Vector v)
          Optimized version of distance metric for sparse vectors.
 double distance(Vector v1, Vector v2)
          Returns the distance metric applied to the arguments
 
Methods inherited from interface org.apache.mahout.common.parameters.Parametered
configure, createParameters, getParameters
 

Method Detail

distance

double distance(Vector v1,
                Vector v2)
Returns the distance metric applied to the arguments

Parameters:
v1 - a Vector defining a multidimensional point in some feature space
v2 - a Vector defining a multidimensional point in some feature space
Returns:
a scalar doubles of the distance

distance

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