multilabel_classification

Methods to detect data and label issues in multi-label classification datasets.

In multi-class classification, each example in the dataset belongs to exactly 1 out of K classes (e.g. if classifying animals as: {dog, cat, rat}).

In multi-label classification, each example in the dataset can belong to 1 or more classes (out of K possible classes), or none of the classes at all (e.g. if classifying animals as: {predator, pet, reptile}).

• filter
  • find_label_issues()
  • find_multilabel_issues_per_class()
• rank
  • get_label_quality_scores()
  • get_label_quality_scores_per_class()
• dataset
  • common_multilabel_issues()
  • rank_classes_by_multilabel_quality()
  • overall_multilabel_health_score()
  • multilabel_health_summary()