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

Class AUnboundedRegressionMeasure

java.lang.Object

ai.libs.jaicore.ml.classification.loss.dataset.APredictionPerformanceMeasure<java.lang.Double,org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction>

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

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

All Implemented Interfaces:

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

Direct Known Subclasses:

LinearMeanSquaredError, MeanAbsoluteError, MeanSquaredError, MeanSquaredLogarithmicMeanSquaredError, QuadraticQuadraticError, WeightedAbsoluteError, WeightedAsymmetricAbsoluteError

public abstract class AUnboundedRegressionMeasure
extends ARegressionMeasure

Constructor Summary

Constructors

Constructor	Description
AUnboundedRegressionMeasure()

Method Summary

Modifier and Type	Method	Description
double	loss(java.util.List<? extends java.lang.Double> expected, java.util.List<? extends org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction> predicted)	If this performance measure is originally a score function its score is transformed into a loss by multiplying the score with -1.
double	score(java.util.List<? extends java.lang.Double> expected, java.util.List<? extends org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction> predicted)	If this performance measure is originally a loss function its loss is transformed into a score by multiplying the loss with -1.

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

averageInstanceWiseLoss, averageInstanceWiseScore, checkConsistency, loss, 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

Constructor Detail

AUnboundedRegressionMeasure

public AUnboundedRegressionMeasure()

Method Detail

loss

public double loss(java.util.List<? extends java.lang.Double> expected,
                   java.util.List<? extends org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction> predicted)

Description copied from class: APredictionPerformanceMeasure

If this performance measure is originally a score function its score is transformed into a loss by multiplying the score with -1. (loss=-score).

Specified by:

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

Overrides:

loss in class APredictionPerformanceMeasure<java.lang.Double,org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction>

score

public double score(java.util.List<? extends java.lang.Double> expected,
                    java.util.List<? extends org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction> predicted)

Description copied from class: APredictionPerformanceMeasure

If this performance measure is originally a loss function its loss is transformed into a score by multiplying the loss with -1. (score=-loss).

Specified by:

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

Overrides:

score in class APredictionPerformanceMeasure<java.lang.Double,org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction>