smile.validation

Class MCC

java.lang.Object

smile.validation.MCC

All Implemented Interfaces:

ClassificationMeasure

public class MCC
extends java.lang.Object
implements ClassificationMeasure

Matthews correlation coefficient.The MCC is in essence a correlation coefficient between the observed and predicted binary classifications It is considered as a balanced measure for binary classification, even in unbalanced data sets. It varies between -1 (perfect disagreement) and +1 (perfect agreement). When it is 0, the model is not better then random.

Field Summary

Fields

Modifier and Type	Field and Description
static MCC	instance

Constructor Summary

Constructors

Constructor and Description
MCC()

Method Summary

Modifier and Type	Method and Description
double	measure(int[] truth, int[] prediction) Returns an index to measure the quality of classification.
static double	of(int[] truth, int[] prediction) Calculates Matthews correlation coefficient.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

instance

public static final MCC instance

Constructor Detail

MCC

public MCC()

Method Detail

measure

public double measure(int[] truth,
                      int[] prediction)

Description copied from interface: ClassificationMeasure

Returns an index to measure the quality of classification.

Specified by:

measure in interface ClassificationMeasure

Parameters:

truth - the true class labels.

prediction - the predicted class labels.

of

public static double of(int[] truth,
                        int[] prediction)

Calculates Matthews correlation coefficient.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object