code:model_selection
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| + | The simplest form of model evaluation uses a validation/test set: | ||
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| + | <code python> | ||
| + | In [9]: X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.4, random_state=0) | ||
| + | |||
| + | In [10]: classifier = svm.SVC(kernel='linear', C=1).fit(X_train, y_train) | ||
| + | |||
| + | In [11]: classifier.score(X_test, y_test) | ||
| + | Out[11]: 0.7592592592592593 | ||
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| + | |||
| + | </code> | ||
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code/model_selection.txt ยท Last modified: 2016/10/06 14:58 by asa
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