smile.math.distance

Class MahalanobisDistance

java.lang.Object

smile.math.distance.MahalanobisDistance

All Implemented Interfaces:

Distance<double[]>, Metric<double[]>

public class MahalanobisDistance
extends Object
implements Metric<double[]>

In statistics, Mahalanobis distance is based on correlations between variables by which different patterns can be identified and analyzed. It is a useful way of determining similarity of an unknown sample set to a known one. It differs from Euclidean distance in that it takes into account the correlations of the data set and is scale-invariant, i.e. not dependent on the scale of measurements.

Author:

Haifeng Li

Constructor Summary

Constructors

Constructor and Description
MahalanobisDistance(double[][] cov) Constructor with given covariance matrix.

Method Summary

Modifier and Type	Method and Description
double	d(double[] x, double[] y) Returns the distance measure between two objects.
String	toString()

Methods inherited from class java.lang.Object

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

Constructor Detail

MahalanobisDistance

public MahalanobisDistance(double[][] cov)

Constructor with given covariance matrix.

Method Detail

toString

public String toString()

Overrides:

toString in class Object

d

public double d(double[] x,
                double[] y)

Description copied from interface: Distance

Returns the distance measure between two objects.

Specified by:

d in interface Distance<double[]>