de.tud.ke.mrapp.rulelearning.core.heuristics

Class Recall

java.lang.Object

de.tud.ke.mrapp.rulelearning.core.heuristics.Heuristic

de.tud.ke.mrapp.rulelearning.core.heuristics.Recall

All Implemented Interfaces:

java.io.Serializable

public class Recall
extends Heuristic

A heuristic that calculates the recall (also known as true positive rate) of predictions based on a ConfusionMatrix. Recall calculates as the fraction of correct positive predictions (TP) among all positive examples (TP + FN).

Since:

0.1.0

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class de.tud.ke.mrapp.rulelearning.core.heuristics.Heuristic

Heuristic.Comparator<T extends Measurable>

Constructor Summary

Constructors

Constructor and Description
Recall()

Method Summary

Modifier and Type	Method and Description
double	evaluate(@NotNull ConfusionMatrix confusionMatrix) Calculates a heuristic values based on a ConfusionMatrix.
boolean	isGainMetric() Returns, whether the heuristic is a gain metric, i.e.
double	maxValue() Returns the maximum heuristic value that may be calculated by the heuristic.
double	minValue() Returns the minimum heuristic value that may be calculated by the heuristic.
java.lang.String	toString()

Methods inherited from class de.tud.ke.mrapp.rulelearning.core.heuristics.Heuristic

equals, evaluate, hashCode, isLossMetric

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

Recall

public Recall()

Method Detail

evaluate

public double evaluate(@NotNull
                       @NotNull ConfusionMatrix confusionMatrix)

Description copied from class: Heuristic

Calculates a heuristic values based on a ConfusionMatrix.

Specified by:

evaluate in class Heuristic

Parameters:

confusionMatrix - The confusion matrix to be evaluated

Returns:

The heuristic value that has been calculated

isGainMetric

public boolean isGainMetric()

Description copied from class: Heuristic

Returns, whether the heuristic is a gain metric, i.e. that greater heuristic values are considered to be better than lower heuristic values, or not.

Specified by:

isGainMetric in class Heuristic

Returns:

True, if the heuristic is a gain metric, false otherwise

maxValue

public double maxValue()

Description copied from class: Heuristic

Returns the maximum heuristic value that may be calculated by the heuristic.

Specified by:

maxValue in class Heuristic

Returns:

The maximum heuristic value that may be calculated by the heuristic

minValue

public double minValue()

Description copied from class: Heuristic

Returns the minimum heuristic value that may be calculated by the heuristic.

Specified by:

minValue in class Heuristic

Returns:

The minimum heuristic value that may be calculated by the heuristic

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object