File Content: digits_classification_exercise.py """ ================================ Digits Classification Exercise ================================ A tutorial exercise regarding the use of classification techniques on the Digits dataset. This exercise is used in the :ref:`clf_tut` part of the :ref:`supervised_learning_tut` section of the :ref:`stat_learn_tut_index`. """ print(__doc__) from sklearn import datasets, neighbors, linear_model digits = datasets.load_digits() X_digits = digits.data y_digits = digits.target n_samples = len(X_digits) X_train = X_digits[:.9 * n_samples] y_train = y_digits[:.9 * n_samples] X_test = X_digits[.9 * n_samples:] y_test = y_digits[.9 * n_samples:] knn = neighbors.KNeighborsClassifier() logistic = linear_model.LogisticRegression() print('KNN score: %f' % knn.fit(X_train, y_train).score(X_test, y_test)) print('LogisticRegression score: %f' % logistic.fit(X_train, y_train).score(X_test, y_test)) Submit