************How to find parameters using GridSearchCV for Regression*************
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Results from Grid Search
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The best estimator across ALL searched params:
GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
learning_rate=0.03, loss='ls', max_depth=6, max_features=None,
max_leaf_nodes=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=1000, n_iter_no_change=None, presort='auto',
random_state=None, subsample=0.2, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
The best score across ALL searched params:
0.8556259467422789
The best parameters across ALL searched params:
{'learning_rate': 0.03, 'max_depth': 6, 'n_estimators': 1000, 'subsample': 0.2}
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