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