11_random forest python - smart1004/doc GitHub Wiki

{'min_impurity_decrease': [0.0], 'min_samples_leaf': [5], 'min_samples_split': [2], 'n_estimators': [301],'random_state': [2019], 'bootstrap': [True], 'criterion': ['mse'], 'n_jobs': [-1]}

{'random_state': [42], 'bootstrap': [True], 'criterion': ['mse'], 'min_impurity_decrease': [0.0], 'min_samples_leaf': [4], 'min_samples_split':[ 2], 'n_estimators': [301,501], 'n_jobs': [-1]}

{ 'bootstrap': [True], 'max_depth': [80, 90, 100, 110], 'max_features': [2, 3], 'min_samples_leaf': [3, 4, 5], 'min_samples_split': [2, 8, 10], 'n_estimators': [200, 300], 'n_jobs': [-1]}

randomforestregressor gridsearchcv

https://towardsdatascience.com/hyperparameter-tuning-the-random-forest-in-python-using-scikit-learn-28d2aa77dd74

{ 'n_estimators':[200, 300], 'n_jobs': [-1] }

'max_features': ['auto', 'sqrt'] {'bootstrap': [True, False], 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, None], 'max_features': ['auto', 'sqrt'], 'min_samples_leaf': [1, 2, 4], 'min_samples_split': [2, 5, 10], 'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000]}

https://partrita.github.io/posts/random-forest-python/