*********How to find parameters using RandomizedSearchCV for Regression**********
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Results from Random Search
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The best estimator across ALL searched params:
GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
learning_rate=0.05135418594969088, loss='ls', max_depth=5,
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=944,
n_iter_no_change=None, presort='auto', random_state=None,
subsample=0.3717049745395081, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
The best score across ALL searched params:
0.8116426451217794
The best parameters across ALL searched params:
{'learning_rate': 0.05135418594969088, 'max_depth': 5, 'n_estimators': 944, 'subsample': 0.3717049745395081}
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