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

Class FMeasure

java.lang.Object

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

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

All Implemented Interfaces:

java.io.Serializable

public class FMeasure
extends Heuristic

A heuristic that calculates the F-Measure of predictions based on a ConfusionMatrix. The F-Measure trades-off precision (if beta = 0) and recall (if m approaches Double.POSITIVE_INFINITY).

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
FMeasure() Creates the default f-measure with the beta-parameter set to 1 (also known as F1-measure).
FMeasure(double beta) Creates a new f-measure with a specific beta-parameter.

Method Summary

Modifier and Type	Method and Description
boolean	equals(java.lang.Object obj)
double	evaluate(@NotNull ConfusionMatrix confusionMatrix) Calculates a heuristic values based on a ConfusionMatrix.
double	getBeta() Returns the value of the beta-parameter.
int	hashCode()
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

evaluate, isLossMetric

Methods inherited from class java.lang.Object

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

Constructor Detail

FMeasure

public FMeasure()

Creates the default f-measure with the beta-parameter set to 1 (also known as F1-measure).

FMeasure

public FMeasure(double beta)

Creates a new f-measure with a specific beta-parameter.

Parameters:

beta - The value of the beta-parameter

Method Detail

getBeta

public double getBeta()

Returns the value of the beta-parameter.

Returns:

The value of the beta-parameter

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

hashCode

public int hashCode()

Overrides:

hashCode in class Heuristic

equals

public boolean equals(java.lang.Object obj)

Overrides:

equals in class Heuristic