Run 10434611

Task 211237 (Supervised Regression) dataset-autoHorse_fixed Uploaded 19-12-2019 by George Volkov
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

sklearn.ensemble.forest.RandomForestRegressor(2)	A random forest regressor. A random forest is a meta estimator that fits a number of classifying decision trees on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is always the same as the original input sample size but the samples are drawn with replacement if `bootstrap=True` (default).
sklearn.ensemble.forest.RandomForestRegressor(2)_bootstrap	true
sklearn.ensemble.forest.RandomForestRegressor(2)_criterion	"mse"
sklearn.ensemble.forest.RandomForestRegressor(2)_max_depth	null
sklearn.ensemble.forest.RandomForestRegressor(2)_max_features	"auto"
sklearn.ensemble.forest.RandomForestRegressor(2)_max_leaf_nodes	null
sklearn.ensemble.forest.RandomForestRegressor(2)_min_impurity_decrease	0.0
sklearn.ensemble.forest.RandomForestRegressor(2)_min_impurity_split	null
sklearn.ensemble.forest.RandomForestRegressor(2)_min_samples_leaf	1
sklearn.ensemble.forest.RandomForestRegressor(2)_min_samples_split	2
sklearn.ensemble.forest.RandomForestRegressor(2)_min_weight_fraction_leaf	0.0
sklearn.ensemble.forest.RandomForestRegressor(2)_n_estimators	100
sklearn.ensemble.forest.RandomForestRegressor(2)_n_jobs	null
sklearn.ensemble.forest.RandomForestRegressor(2)_oob_score	false
sklearn.ensemble.forest.RandomForestRegressor(2)_random_state	63139
sklearn.ensemble.forest.RandomForestRegressor(2)_verbose	0
sklearn.ensemble.forest.RandomForestRegressor(2)_warm_start	false