Package ai.libs.jaicore.ml.core.evaluation.measure.multilabel
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Interface Summary Interface Description IMultilabelMeasure Interface for measures dealing with multilabel data. -
Class Summary Class Description ADecomposableMultilabelMeasure AutoMekaGGPFitness AutoMEKAGGPFitnessMeasure Fitness function for a linear combination of 4 well-known multi-label metrics: ExactMatch, Hamming, Rank and F1MacroAverageL.AutoMEKAGGPFitnessMeasureLoss Measure combining exact match, hamming loss, f1macroavgL and rankloss.ExactMatchAccuracy Computes the exact match of the predicted multi label vector and the expected.ExactMatchLoss F1MacroAverageL F1MacroAverageLLoss Compute the inverted F1 measure macro averaged by label.HammingAccuracy Measure for computing how similar two double vectors are according to hamming distance.HammingLoss InstanceWiseF1 Instance-wise F1 measure for multi-label classifiers.InstanceWiseF1AsLoss The F1 Macro Averaged by the number of instances measure.JaccardLoss JaccardScore RankLoss RankScore -
Enum Summary Enum Description EMultilabelPerformanceMeasure