ClassificationMultilabelPrimaryMetrics type

Defines values for ClassificationMultilabelPrimaryMetrics.
KnownClassificationMultilabelPrimaryMetrics can be used interchangeably with ClassificationMultilabelPrimaryMetrics, this enum contains the known values that the service supports.

Known values supported by the service

AUCWeighted: AUC is the Area under the curve. This metric represents arithmetic mean of the score for each class, weighted by the number of true instances in each class.
Accuracy: Accuracy is the ratio of predictions that exactly match the true class labels.
NormMacroRecall: Normalized macro recall is recall macro-averaged and normalized, so that random performance has a score of 0, and perfect performance has a score of 1.
AveragePrecisionScoreWeighted: The arithmetic mean of the average precision score for each class, weighted by the number of true instances in each class.
PrecisionScoreWeighted: The arithmetic mean of precision for each class, weighted by number of true instances in each class.
IOU: Intersection Over Union. Intersection of predictions divided by union of predictions.