ai.libs.jaicore.ml.core.evaluation.measure.singlelabel

Class MeanSquaredErrorLoss

java.lang.Object

ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableMeasure<I,java.lang.Double>

ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableDoubleMeasure<java.lang.Double>

ai.libs.jaicore.ml.core.evaluation.measure.singlelabel.ASquaredErrorLoss

ai.libs.jaicore.ml.core.evaluation.measure.singlelabel.MeanSquaredErrorLoss

All Implemented Interfaces:

IMeasure<java.lang.Double,java.lang.Double>, java.io.Serializable

public class MeanSquaredErrorLoss
extends ASquaredErrorLoss

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MeanSquaredErrorLoss()

Method Summary

Modifier and Type	Method and Description
java.lang.Double	calculateMeasure(java.lang.Double actual, java.lang.Double expected) Computes the measure for a measured input actual and the expected outcome expected.

Methods inherited from class ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableDoubleMeasure

calculateAvgMeasure

Methods inherited from class ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableMeasure

calculateMeasure, calculateMeasure

Methods inherited from class java.lang.Object

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

Constructor Detail

MeanSquaredErrorLoss

public MeanSquaredErrorLoss()

Method Detail

calculateMeasure

public java.lang.Double calculateMeasure(java.lang.Double actual,
                                         java.lang.Double expected)

Description copied from interface: IMeasure

Computes the measure for a measured input actual and the expected outcome expected.

Specified by:

calculateMeasure in interface IMeasure<java.lang.Double,java.lang.Double>

Overrides:

calculateMeasure in class ASquaredErrorLoss

Parameters:

actual - The actually available values.

expected - The expected values to compare the actual values with.

Returns:

The return value of the measure.