| @@ 42-54 (lines=13) @@ | ||
| 39 | return scores.mean() | |
| 40 | ||
| 41 | ||
| 42 | def model_gbc(opt): | |
| 43 | gbc = GradientBoostingClassifier( | |
| 44 | n_estimators=opt["n_estimators"], | |
| 45 | learning_rate=opt["learning_rate"], | |
| 46 | max_depth=opt["max_depth"], | |
| 47 | min_samples_split=opt["min_samples_split"], | |
| 48 | min_samples_leaf=opt["min_samples_leaf"], | |
| 49 | subsample=opt["subsample"], | |
| 50 | max_features=opt["max_features"], | |
| 51 | ) | |
| 52 | scores = cross_val_score(gbc, X, y, cv=3) | |
| 53 | ||
| 54 | return scores.mean() | |
| 55 | ||
| 56 | ||
| 57 | search_space_etc = { | |
| @@ 42-54 (lines=13) @@ | ||
| 39 | return scores.mean() | |
| 40 | ||
| 41 | ||
| 42 | def model_gbc(opt): | |
| 43 | gbc = GradientBoostingClassifier( | |
| 44 | n_estimators=opt["n_estimators"], | |
| 45 | learning_rate=opt["learning_rate"], | |
| 46 | max_depth=opt["max_depth"], | |
| 47 | min_samples_split=opt["min_samples_split"], | |
| 48 | min_samples_leaf=opt["min_samples_leaf"], | |
| 49 | subsample=opt["subsample"], | |
| 50 | max_features=opt["max_features"], | |
| 51 | ) | |
| 52 | scores = cross_val_score(gbc, X, y, cv=3) | |
| 53 | ||
| 54 | return scores.mean() | |
| 55 | ||
| 56 | ||
| 57 | search_space_etc = { | |