FEA D2 Brier Score #28971
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FEA D2 Brier Score #28971
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| }, | ||
| prefer_skip_nested_validation=True, | ||
| ) | ||
| def d2_brier_score(y_true, y_proba, *, sample_weight=None, pos_label=None): |
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Suggested change
| def d2_brier_score(y_true, y_proba, *, sample_weight=None, pos_label=None): | |
| def d2_brier_score(y_true, y_proba, *, sample_weight=None, labels=None): |
This should be able to handle multiclass, too. See log_loss.
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How are we supposed to extract the pos_label to pass to brier_score_loss?
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| y_true = column_or_1d(y_true) | ||
| positive_label = _get_positive_label_for_brier_score(y_true, pos_label) | ||
| weights = _check_sample_weight(sample_weight, y_true) | ||
| positive_prob = np.sum((y_true == positive_label) * weights) / np.sum(weights) | ||
| y_proba_ref = np.full(y_true.shape, positive_prob) |
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This should be the same code as in d2_log_loss.
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| def _get_positive_label_for_brier_score(y_true, pos_label=None): | ||
| try: | ||
| pos_label = _check_pos_label_consistency(pos_label, y_true) | ||
| except ValueError: | ||
| classes = np.unique(y_true) | ||
| if classes.dtype.kind not in ("O", "U", "S"): | ||
| # for backward compatibility, if classes are not string then | ||
| # `pos_label` will correspond to the greater label | ||
| pos_label = classes[-1] | ||
| else: | ||
| raise | ||
|
|
||
| return pos_label |
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Suggested change
| def _get_positive_label_for_brier_score(y_true, pos_label=None): | |
| try: | |
| pos_label = _check_pos_label_consistency(pos_label, y_true) | |
| except ValueError: | |
| classes = np.unique(y_true) | |
| if classes.dtype.kind not in ("O", "U", "S"): | |
| # for backward compatibility, if classes are not string then | |
| # `pos_label` will correspond to the greater label | |
| pos_label = classes[-1] | |
| else: | |
| raise | |
| return pos_label |
|
#22046 seems like a blocker |
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Reference Issues/PRs
Closes #20943
What does this implement/fix? Explain your changes.
Any other comments?
CC: @lorentzenchr