smile.math.distance

Class MahalanobisDistance

java.lang.Object

smile.math.distance.MahalanobisDistance

All Implemented Interfaces:

java.io.Serializable, java.util.function.ToDoubleBiFunction<double[],double[]>, Distance<double[]>, Metric<double[]>

public class MahalanobisDistance
extends java.lang.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.

See Also:

Serialized Form

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.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Methods inherited from interface smile.math.distance.Distance

apply, applyAsDouble, D, D

Constructor Detail

MahalanobisDistance

public MahalanobisDistance(double[][] cov)

Constructor with given covariance matrix.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.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[]>