ClassificationMultilabelPrimaryMetrics

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 is the ratio of predictions that exactly match the true class labels.

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.

The arithmetic mean of the average precision score for each class, weighted by the number of true instances in each class.

The arithmetic mean of precision for each class, weighted by number of true instances in each class.

Intersection Over Union. Intersection of predictions divided by union of predictions.

Returns a representation of an immutable list of all enum entries, in the order they're declared.

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Returns an array containing the constants of this enum type, in the order they're declared.