Class Precision

java.lang.Object

smile.validation.metric.Precision

All Implemented Interfaces:

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

public class Precision
extends Object
implements ClassificationMetric

The precision or positive predictive value (PPV) is ratio of true positives to combined true and false positives, which is different from sensitivity.

    PPV = TP / (TP + FP)

See Also:

• Serialized Form

Field Summary

Fields

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

Constructor Summary

Constructors

Constructor	Description
Precision()	Constructor.
Precision(Averaging strategy)	Constructor.

Method Summary

Modifier and Type	Method	Description
static double	of(int[] truth, int[] prediction)	Calculates the precision of binary classification.
static double	of(int[] truth, int[] prediction, Averaging strategy)	Calculates the precision.
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 Precision instance

Default instance.

Constructor Details

Precision

public Precision()

Constructor.

Precision

public Precision(Averaging strategy)

Constructor.

Parameters:

strategy - The aggregating strategy for multi-classes.

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.

toString

public String toString()

Overrides:

toString in class Object

of

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

Calculates the precision of binary classification.

Parameters:

truth - the ground truth.

prediction - the prediction.

Returns:

the metric.

of

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

Calculates the precision.

Parameters:

truth - the ground truth.

prediction - the prediction.

strategy - The aggregating strategy for multi-classes.

Returns:

the metric.