21 lines
885 B
Python
21 lines
885 B
Python
"""
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The :mod:`sklearn.metrics.cluster` submodule contains evaluation metrics for
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cluster analysis results. There are two forms of evaluation:
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- supervised, which uses a ground truth class values for each sample.
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- unsupervised, which does not and measures the 'quality' of the model itself.
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"""
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from .supervised import adjusted_mutual_info_score
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from .supervised import normalized_mutual_info_score
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from .supervised import adjusted_rand_score
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from .supervised import completeness_score
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from .supervised import contingency_matrix
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from .supervised import expected_mutual_information
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from .supervised import homogeneity_completeness_v_measure
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from .supervised import homogeneity_score
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from .supervised import mutual_info_score
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from .supervised import v_measure_score
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from .supervised import entropy
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from .unsupervised import silhouette_samples
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from .unsupervised import silhouette_score
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