org.apache.mahout.common.distance

Class MinkowskiDistanceMeasure

java.lang.Object

org.apache.mahout.common.distance.MinkowskiDistanceMeasure

All Implemented Interfaces:

DistanceMeasure, Parametered

public class MinkowskiDistanceMeasure
extends Object
implements DistanceMeasure

Implement Minkowski distance, a real-valued generalization of the integral L(n) distances: Manhattan = L1, Euclidean = L2. For high numbers of dimensions, very high exponents give more useful distances. Note: Math.pow is clever about integer-valued doubles.

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
MinkowskiDistanceMeasure()
MinkowskiDistanceMeasure(double exponent)

Method Summary

Modifier and Type	Method and Description
void	configure(org.apache.hadoop.conf.Configuration jobConf)
void	createParameters(String prefix, org.apache.hadoop.conf.Configuration conf) EXPERT: consumers should never have to call this method.
double	distance(double centroidLengthSquare, Vector centroid, Vector v) Optimized version of distance metric for sparse vectors.
double	distance(Vector v1, Vector v2) Math.pow is clever about integer-valued doubles
double	getExponent()
Collection<Parameter<?>>	getParameters()
void	setExponent(double exponent)

Methods inherited from class java.lang.Object

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

Constructor Detail

MinkowskiDistanceMeasure

public MinkowskiDistanceMeasure()

MinkowskiDistanceMeasure

public MinkowskiDistanceMeasure(double exponent)

Method Detail

createParameters

public void createParameters(String prefix,
                             org.apache.hadoop.conf.Configuration conf)

Description copied from interface: Parametered

EXPERT: consumers should never have to call this method. It would be friendly visible to Parametered.ParameteredGeneralizations if java supported it. Calling this method should create a new list of parameters and is called

Specified by:

createParameters in interface Parametered

Parameters:

prefix - ends with a dot if not empty.

conf - configuration used for retrieving values

See Also:

invoking method, invoking method

getParameters

public Collection<Parameter<?>> getParameters()

Specified by:

getParameters in interface Parametered

configure

public void configure(org.apache.hadoop.conf.Configuration jobConf)

Specified by:

configure in interface Parametered

getExponent

public double getExponent()

setExponent

public void setExponent(double exponent)

distance

public double distance(Vector v1,
                       Vector v2)

Math.pow is clever about integer-valued doubles

Specified by:

distance in interface DistanceMeasure

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

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.

Specified by:

distance in interface DistanceMeasure

Parameters:

centroidLengthSquare - Square of the length of centroid

centroid - Centroid vector