Add the n_feature_parts parameter to the supervised estimators
#544
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folmos-at-orange
approved these changes
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.
- KhiopsClassifier, KhiopsRegressor and KhiopsEncoder
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Feb 9, 2026
| "specific_pairs": [("age", "race")], | ||
| "all_possible_pairs": False, | ||
| "construction_rules": ["TableMode", "TableSelection"], | ||
| "max_parts": 0, |
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I'm not sure in this testcase we need to test that the default value provided to the Core API is correct or unchanged via sklearn. Indeed, in this testcase we test that the parameters are correctly passed from the sklearn code to the core API.
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Fixes #533
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