a good sol ution. However, a pooling kernel with the data for Machine Learning Project print(np.sqrt(-mean_score), params) 63669.05791727153 {'max_features': 2, 'n_estimators': 3} 52740.98248528835 {'max_features': 4, 'n_estimators': 10} 59470.399594730654 {'bootstrap': False, 'max_features': 2, 'n_estimators': 30} 57869.25504027614 {'max_features': 8, 'n_estimators': 3} 51009.51445842374 {'bootstrap': False, 'max_features': 2, 'n_estimators': 3} 55627.16171305252 {'max_features': 2, 'n_estimators': 3} 54658.14484390074 {'bootstrap': False, 'max_features': 3, 'n_estimators': 3} 51711.09443660957 {'max_features': 8, 'n_estimators': 30} 62895.088889905004 {'bootstrap': False, 'max_features': 4, 'n_estimators': 3} 52725.01091081235 {'bootstrap': False, 'max_features': 4, 'n_estimators': 3} 54658.14484390074 {'bootstrap': False,
Bearnaise