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TEST4fd1adc95dsklearn.ensemble._forest.RandomForestClassifier

TEST4fd1adc95dsklearn.ensemble._forest.RandomForestClassifier

Visibility: public Uploaded 18-10-2024 by Continuous Integration sklearn==1.1.3 numpy>=1.17.3 scipy>=1.3.2 joblib>=1.0.0 threadpoolctl>=2.0.0 0 runs
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  • openml-python python scikit-learn sklearn sklearn_1.1.3
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A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the `max_samples` parameter if `bootstrap=True` (default), otherwise the whole dataset is used to build each tree.

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