20 lines
545 B
Python
20 lines
545 B
Python
from scikits.learn import datasets, neighbors, linear_model
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digits = datasets.load_digits()
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X_digits = digits.data
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y_digits = digits.target
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n_samples = len(X_digits)
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X_train = X_digits[:.9*n_samples]
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y_train = y_digits[:.9*n_samples]
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X_test = X_digits[.9*n_samples:]
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y_test = y_digits[.9*n_samples:]
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knn = neighbors.NeighborsClassifier()
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logistic = linear_model.LogisticRegression()
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print 'KNN score:', knn.fit(X_train, y_train).score(X_test, y_test)
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print 'LogisticRegression score:', logistic.fit(X_train, y_train).score(X_test, y_test)
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