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randomsubgroups._randomsubgroups.RandomSubgroupClassifier

randomsubgroups._randomsubgroups.RandomSubgroupClassifier

Visibility: public Uploaded 21-10-2020 by Claudio Rebelo Sá sklearn==0.23.1 numpy>=1.6.1 scipy>=0.9 9 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...

Parameters

bootstrapdefault: true
intervals_onlydefault: true
max_depthdefault: 1
max_featuresdefault: "auto"
max_samplesdefault: null
n_binsdefault: 5
n_estimatorsdefault: 100
n_jobsdefault: null
quality_function_weightdefault: 0.5
result_set_sizedefault: 1
search_strategydefault: "bestfirst"
verbosedefault: 0

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