Package ai.libs.jaicore.ml.regression.loss.dataset

Class MeanSquaredError

java.lang.Object

ai.libs.jaicore.ml.classification.loss.dataset.APredictionPerformanceMeasure<java.lang.Double,java.lang.Double>

ai.libs.jaicore.ml.regression.loss.dataset.ARegressionMeasure

ai.libs.jaicore.ml.regression.loss.dataset.MeanSquaredError

All Implemented Interfaces:

org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicHomogeneousPredictionPerformanceMeasure<java.lang.Double>, org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure<java.lang.Double,java.lang.Double>

public class MeanSquaredError
extends ARegressionMeasure

Constructor Summary

Constructors

Constructor	Description
MeanSquaredError()

Method Summary

Modifier and Type	Method	Description
double	loss(java.util.List<? extends java.lang.Double> expected, java.util.List<? extends java.lang.Double> actual)

Methods inherited from class ai.libs.jaicore.ml.classification.loss.dataset.APredictionPerformanceMeasure

averageInstanceWiseLoss, averageInstanceWiseScore, checkConsistency, loss, score, score

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure

loss, score, score

Constructor Detail

MeanSquaredError

public MeanSquaredError()

Method Detail

loss

public double loss(java.util.List<? extends java.lang.Double> expected,
                   java.util.List<? extends java.lang.Double> actual)

Specified by:

loss in interface org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure<java.lang.Double,java.lang.Double>

Overrides:

loss in class APredictionPerformanceMeasure<java.lang.Double,java.lang.Double>