RootMeanSquaredError (jaicore-ml 0.2.5 API)

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.RootMeanSquaredError

All Implemented Interfaces:

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

Constructor Summary

Constructors
Constructor Description

RootMeanSquaredError()

Method Summary

All Methods Instance Methods Concrete Methods
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.

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
  - RootMeanSquaredError
```
public RootMeanSquaredError()
```
- 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>