GridSearchCV with Random Forest with print result
Sat Jun 11 2022 10:59:22 GMT+0000 (Coordinated Universal Time)
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@abhin__dev
# Conduct search for best params while running cross-validation (GridSearchCV)
rf = RandomForestClassifier()
parameters = {
'n_estimators': [2**i for i in range(3, 6)],
'max_depth': [2, 4, 8, 16, 32, None]
}
cv = GridSearchCV(rf, parameters, cv=3)
cv.fit(train_features, train_labels.values.ravel())
#Print Result
def print_results(results):
print('BEST PARAMS: {}\n'.format(results.best_params_))
means = results.cv_results_['mean_test_score']
stds = results.cv_results_['std_test_score']
for mean, std, params in zip(means, stds, results.cv_results_['params']):
print('{} (+/-{}) for {}'.format(round(mean, 3), round(std * 2, 3), params))
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