In this recipe, we explore multilabel classification MultilabelMetrics in Spark 2.0 which should not be mixed up with the previous recipe dealing with multiclass classification MulticlassMetrics. The key to exploring this recipe is to concentrate on evaluation metrics such as Hamming loss, accuracy, f1-measure, and so on, and what they measure.
Multilabel classification model evaluation using Spark 2.0
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