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

Class RootMeanSquaredErrorLoss

  • All Implemented Interfaces:
    IMeasure<java.lang.Double,​java.lang.Double>, java.io.Serializable
    public class RootMeanSquaredErrorLoss
extends ASquaredErrorLoss
    The root mean squared loss function. This loss function computes the sum of differences of expected/actual pairs, divides this by the number of observations, and takes the square root.
    See Also:
    Serialized Form

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      java.lang.Double calculateAvgMeasure​(java.util.List<java.lang.Double> actual, java.util.List<java.lang.Double> expected)
      Computes the measure for lists of input actual and the expected outcome expected and aggregates the measured values with the mean, as this is the most frequently used aggregate function.

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • RootMeanSquaredErrorLoss

        public RootMeanSquaredErrorLoss()

    • Method Detail

      • calculateAvgMeasure

        public java.lang.Double calculateAvgMeasure​(java.util.List<java.lang.Double> actual,
                                            java.util.List<java.lang.Double> expected)
        Description copied from interface: IMeasure
        Computes the measure for lists of input actual and the expected outcome expected and aggregates the measured values with the mean, as this is the most frequently used aggregate function.
        Specified by:
        calculateAvgMeasure in interface IMeasure<java.lang.Double,​java.lang.Double>
        Overrides:
        calculateAvgMeasure in class ADecomposableDoubleMeasure<java.lang.Double>
        Parameters:
        actual - The list of actually available values.
        expected - The list of expected values to compare the actual values with.
        Returns:
        The mean of return values as output by the instance-wise measure.