chore: import upstream snapshot with attribution
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dataset
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.. automodule:: cleanlab.multilabel_classification.dataset
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:autosummary:
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:members:
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:undoc-members:
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filter
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======
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.. automodule:: cleanlab.multilabel_classification.filter
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:autosummary:
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:members:
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:undoc-members:
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multilabel_classification
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=========================
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Methods to detect data and label issues in multi-label classification datasets.
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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}).
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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}).
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.. automodule:: cleanlab.multilabel_classification
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:autosummary:
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:members:
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:undoc-members:
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:show-inheritance:
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.. toctree::
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filter
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rank
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dataset
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rank
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====
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.. automodule:: cleanlab.multilabel_classification.rank
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:autosummary:
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:members:
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:undoc-members:
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:show-inheritance:
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