Visibility: public Uploaded 21-10-2020 by Cláudio Rebelo Sá sklearn==0.23.1 numpy>=1.6.1 scipy>=0.9 8 runs
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  • openml-python python random-subgroups_0.1.1 scikit-learn sklearn sklearn_0.23.1
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A random subgroups classifier. A random subgroups classifier is a meta estimator that fits a number subgroups on various sub-samples of the dataset. The sub-sample size is controlled with the `max_samples` parameter if `bootstrap=True` (default), otherwise the whole dataset is used to search for each subgroup. The Parameters ----------- n_estimators : int, default=100 The number of subgroups in the ensemble. max_depth : int, default=1 The maximum depth of the subgroup discovery task. max_features : {"auto", "sqrt", "log2"}, int or float, default="auto" The number of features to consider when looking for the best subgroup: - If int, then consider `max_features` features for each subgroup. - If float, then `max_features` is a fraction and `round(max_features * n_features)` features are considered for each subgroup. - If "auto", then `max_features=sqrt(n_features)`. - If "sqrt", then `max_features=sqrt(n_features)` (same as "auto"). - If "log2", then `max_feature...



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