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

Class ARegressionMeasure

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

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:

AbsoluteError, AsymmetricLoss, AsymmetricLoss2, AUnboundedRegressionMeasure, MeanAbsolutePercentageError, MeanAsymmetricLoss2, MeanPercentageError, MeanSquaredLogarithmicError, MeanSquaredPercentageError, R2, RootMeanSquaredError, RootMeanSquaredLogarithmError, SquaredError

public abstract class ARegressionMeasure
extends APredictionPerformanceMeasure<java.lang.Double,org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction>
implements org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure<java.lang.Double,org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction>

Constructor Summary

Constructors

Constructor	Description
ARegressionMeasure()

Method Summary

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

averageInstanceWiseLoss, averageInstanceWiseScore, checkConsistency, loss, 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, loss, score, score

Constructor Detail

ARegressionMeasure

public ARegressionMeasure()