Class FDR

java.lang.Object

smile.validation.metric.FDR

All Implemented Interfaces:

Serializable, ToDoubleBiFunction<int[],int[]>, ClassificationMetric

public class FDR
extends Object
implements ClassificationMetric

The false discovery rate (FDR) is ratio of false positives to combined true and false positives, which is actually 1 - precision.

    FDR = FP / (TP + FP)

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
static final FDR	instance	Default instance.

Constructor Summary

Constructors

Constructor	Description
FDR()	Constructor.

Method Summary

Modifier and Type	Method	Description
static double	of(int[] truth, int[] prediction)	Calculates the false discovery rate.
double	score(int[] truth, int[] prediction)	Returns a score to measure the quality of classification.
String	toString()

Methods inherited from class Object

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

Methods inherited from interface ClassificationMetric

applyAsDouble

Field Details

instance

public static final FDR instance

Default instance.

Constructor Details

FDR

public FDR()

Constructor.

Method Details

score

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

Description copied from interface: ClassificationMetric

Returns a score to measure the quality of classification.

Specified by:

score in interface ClassificationMetric

Parameters:

truth - the true class labels.

prediction - the predicted class labels.

Returns:

the metric.

of

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

Calculates the false discovery rate.

Parameters:

truth - the ground truth.

prediction - the prediction.

Returns:

the metric.

toString

public String toString()

Overrides:

toString in class Object