Feat/replace random forest #1246
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benjamc
requested changes
Aug 25, 2025
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| @staticmethod | ||
| def get_intensifier( # type: ignore | ||
| scenario: Scenario, |
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I guess the intensifier and initial design are just copy-pasted from the MF facade right? Nothing has changed here?
| n_instances: int, | ||
| lock: threading.Lock, | ||
| ) -> None: | ||
| """Collect predictions from a single estimator. However, we sum the results from all instances""" |
| Validate X whenever one tries to predict, apply, predict_proba. | ||
| It is based on rf regressor from sklearn 1.6.1: | ||
| https://github.com/scikit-learn/scikit-learn/blob/99bf3d8e4eed5ba5db19a1869482a238b6223ffd/sklearn/ensemble/_forest.py#L629 | ||
| However, we add another parameter to allow the model to ignore feature checking (this is done after |
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why would we want to ignore feature checking? add to docstring
| cross_trees_variance: bool = False, | ||
| criterion: str = "squared_error", | ||
| splitter: str = "random", # Should not be changed | ||
| max_depth: int = 2**20, # TODO: HP: None is default in sklearn, here it's 2**20 |
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rewrite comments, afaik there is no TODO. these were the HPs of the previous RF, right?
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in all cases, keep the information somewhere
benjamc
approved these changes
Aug 28, 2025
benjamc
requested changes
Aug 28, 2025
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Replace pyrfr with sklearn's RF