F1MicroAverage (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.F1MicroAverage

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 F1MicroAverage
extends AMultiLabelClassificationMeasure
```

Constructor Summary

Constructors
Constructor Description

F1MicroAverage()

F1MicroAverage(double threshold)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`score(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 loss function its loss is transformed into a score by multiplying the loss 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, loss, 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

- Constructor Detail
  - F1MicroAverage
```
public F1MicroAverage(double threshold)
```
  - F1MicroAverage
```
public F1MicroAverage()
```
- Method Detail
  - score
```
public double score(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 loss function its loss is transformed into a score by multiplying the loss with -1. (score=-loss).
    
    Specified by:
    
    score in interface org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>
    
    Overrides:
    
    score in class APredictionPerformanceMeasure<int[],org.api4.java.ai.ml.classification.multilabel.evaluation.IMultiLabelClassification>