code:model_selection
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code:model_selection [2015/10/05 13:48] asa |
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| + | Next, let'd perform cross-validation: | ||
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| + | <code python> | ||
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| + | In [12]: scores = cross_validation.cross_val_score(classifier, X, y, cv=5, scoring='accuracy') | ||
| + | |||
| + | In [13]: | ||
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| + | In [13]: scores = cross_validation.cross_val_score(classifier, X, y, cv=5, scoring='roc_auc') | ||
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| + | In [14]: # you can also obtain the predictions by cross-validation and then compute the accuracy: | ||
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| + | In [15]: y_predict = cross_validation.cross_val_predict(classifier, X, y, cv=5) | ||
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| + | In [16]: metrics.accuracy_score(y, y_predict) | ||
| + | Out[16]: 0.83703703703703702 | ||
| + | </code> | ||
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code/model_selection.txt ยท Last modified: 2016/10/06 14:58 by asa
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