Add the n_feature_parts parameter to the supervised estimators#544
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Add the n_feature_parts parameter to the supervised estimators#544
n_feature_parts parameter to the supervised estimators#544Conversation
folmos-at-orange
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Feb 4, 2026
| type_error_message("n_feature_parts", self.n_feature_parts, int) | ||
| ) | ||
| if self.n_feature_parts < 0: | ||
| raise ValueError("'n_feature_parts' must be positive") |
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positive -> non-negative
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You are totally right, this reformulation would be more precise. Unfortunatly the message is duplicated many times and for consistency sake it would be required to modify everywhere (in a distinct PR)
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A commit for fixing this would suffice. It is a small change for a PR.
| "specific_pairs": [], | ||
| "all_possible_pairs": False, | ||
| "construction_rules": ["TableMode", "TableSelection"], | ||
| "max_parts": 4, |
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Make one of these tests with an explicit 0
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Yes, I changed the test for KhiopsClassifier "fit" with a monotable : the n_feature_parts parameter was not provided and thus the default value of 0 is set
CHANGELOG.md
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| ## Unreleased | ||
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| ### Added | ||
| - (`sklearn`) A `n_feature_parts` parameter to the supervised estimators |
- KhiopsClassifier, KhiopsRegressor and KhiopsEncoder
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Fixes #533
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main(ormain-v10)Unreleasedsection ofCHANGELOG.md(no date)index.html