ASquaredErrorLoss (jaicore-ml 0.1.6 API)

java.lang.Object
- ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableMeasure<I,java.lang.Double>
- - ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableDoubleMeasure<java.lang.Double>
  - - ai.libs.jaicore.ml.core.evaluation.measure.singlelabel.ASquaredErrorLoss

All Implemented Interfaces:

IMeasure<java.lang.Double,java.lang.Double>, java.io.Serializable

Direct Known Subclasses:

MeanSquaredErrorLoss, RootMeanSquaredErrorLoss
```
public abstract class ASquaredErrorLoss
extends ADecomposableDoubleMeasure<java.lang.Double>
implements java.io.Serializable
```
Measure computing the squared error of two doubles. It can be used to compute the mean squared error.

See Also:

Serialized Form

Constructor Summary

Constructors
Constructor Description

ASquaredErrorLoss()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`java.lang.Double`	`calculateMeasure(java.lang.Double actual, java.lang.Double expected)`	Computes the measure for a measured input actual and the expected outcome expected.

Methods inherited from class ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableDoubleMeasure
calculateAvgMeasure

Methods inherited from class ai.libs.jaicore.ml.core.evaluation.measure.ADecomposableMeasure
calculateMeasure, calculateMeasure

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - ASquaredErrorLoss
```
public ASquaredErrorLoss()
```
- Method Detail
  - calculateMeasure
```
public java.lang.Double calculateMeasure(java.lang.Double actual,
                                         java.lang.Double expected)
```
    Description copied from interface: IMeasure
    
    Computes the measure for a measured input actual and the expected outcome expected.
    
    Specified by:
    
    calculateMeasure in interface IMeasure<java.lang.Double,java.lang.Double>
    
    Parameters:
    
    actual - The actually available values.
    
    expected - The expected values to compare the actual values with.
    
    Returns:
    
    The return value of the measure.