AutoMEKAGGPFitnessMeasureLoss (jaicore-ml 0.2.5 API)

java.lang.Object
- ai.libs.jaicore.ml.classification.loss.dataset.APredictionPerformanceMeasure<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>
- - ai.libs.jaicore.ml.classification.multilabel.evaluation.loss.AMultiLabelClassificationMeasure
  - - ai.libs.jaicore.ml.classification.multilabel.evaluation.loss.AutoMEKAGGPFitnessMeasureLoss

All Implemented Interfaces:

org.api4.java.ai.ml.classification.multilabel.evaluation.loss.IMultiLabelClassificationPredictionPerformanceMeasure, org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>
```
public class AutoMEKAGGPFitnessMeasureLoss
extends AMultiLabelClassificationMeasure
```
Measure combining exact match, hamming loss, f1macroavgL and rankloss. Here implemented in inverse. de Sa, Alex GC, Gisele L. Pappa, and Alex A. Freitas. "Towards a method for automatically selecting and configuring multi-label classification algorithms." Proceedings of the Genetic and Evolutionary Computation Conference Companion. ACM, 2017.

Constructor Summary

Constructors
Constructor Description

AutoMEKAGGPFitnessMeasureLoss()

AutoMEKAGGPFitnessMeasureLoss(double threshold)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`loss(java.util.List<? extends int[]> expected, java.util.List<? extends org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification> 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.multilabel.evaluation.loss.AMultiLabelClassificationMeasure
getThreshold, getThresholdedPredictionAsSet, listToMatrix, listToRelevanceMatrix, listToThresholdedRelevanceMatrix

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
  - AutoMEKAGGPFitnessMeasureLoss
```
public AutoMEKAGGPFitnessMeasureLoss()
```
  - AutoMEKAGGPFitnessMeasureLoss
```
public AutoMEKAGGPFitnessMeasureLoss(double threshold)
```
- Method Detail
  - loss
```
public double loss(java.util.List<? extends int[]> expected,
                   java.util.List<? extends org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification> 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<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>
    
    Overrides:
    
    loss in class APredictionPerformanceMeasure<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>