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OOB Errors for Random Forests — scikit-learn 1....
Record the OOB error for each `n_estimators=i` setting. oob_error...clf . oob_score_ error_rate [ label ] . append (( i , oob_error...scikit-learn.org/stable/auto_examples/ensemble/plot_ensemble_oob.html -
Edgar Allan Poe, ‘The Pingu’. Once upon a night...
medium.com/adams-notebook/edgar-allan-poe-the-pingu-c460d65b9088 -
sklearn.ensemble.BaggingClassifier — scikit-lea...
attribute exists only when oob_score is True. oob_decision_function_...bootstrap_features = False , oob_score = False , warm_start =...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html -
sklearn.ensemble.ExtraTreesRegressor — scikit-l...
attribute exists only when oob_score is True. oob_prediction_ ndarray...= 0.0 , bootstrap = False , oob_score = False , n_jobs = None...scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesRegressor.html -
Gradient Boosting Out-of-Bag estimates — scikit...
label = "OOB loss" , color = oob_color , linestyle = oob_line )...x = oob_best_iter , color = oob_color , linestyle = oob_line...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
Ensemble methods — scikit-learn 1.4.2 documenta...
scikit-learn.org/stable/auto_examples/ensemble/index.html -
sklearn.ensemble.GradientBoostingClassifier — s...
oob_improvement_ ndarray of shape...relative to the previous iteration. oob_improvement_[0] is the improvement...scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html -
sklearn.ensemble.BaggingRegressor — scikit-lear...
attribute exists only when oob_score is True. oob_prediction_ ndarray...bootstrap_features = False , oob_score = False , warm_start =...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingRegressor.html -
sklearn.ensemble.RandomForestRegressor — scikit...
attribute exists only when oob_score is True. oob_prediction_ ndarray... = 0.0 , bootstrap = True , oob_score = False , n_jobs = None...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html