smile.validation

Class AUC

java.lang.Object

smile.validation.AUC

public class AUC
extends java.lang.Object

The area under the curve (AUC). When using normalized units, the area under the curve is equal to the probability that a classifier will rank a randomly chosen positive instance higher than a randomly chosen negative one (assuming 'positive' ranks higher than 'negative').

In statistics, a receiver operating characteristic (ROC), or ROC curve, is a graphical plot that illustrates the performance of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings.

AUC is quite noisy as a classification measure and has some other significant problems in model comparison.

We calculate AUC based on Mann-Whitney U test (https://en.wikipedia.org/wiki/Mann-Whitney_U_test).

Constructor Summary

Constructors

Constructor and Description
AUC()

Method Summary

Modifier and Type	Method and Description
static double	measure(int[] truth, double[] probability) Caulculate AUC for binary classifier.

Methods inherited from class java.lang.Object

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

Constructor Detail

AUC

public AUC()

Method Detail

measure

public static double measure(int[] truth,
                             double[] probability)

Caulculate AUC for binary classifier.

Parameters:

truth - The sample labels

probability - The posterior probability of positive class.

Returns:

AUC