数字分类练习#

关于在Digits数据集上使用分类技术的教程练习。

本练习用于clf_tut部分的supervised_learning_tut章节，属于stat_learn_tut_index。

KNN score: 0.961111
LogisticRegression score: 0.933333

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

from sklearn import datasets, linear_model, neighbors

X_digits, y_digits = datasets.load_digits(return_X_y=True)
X_digits = X_digits / X_digits.max()

n_samples = len(X_digits)

X_train = X_digits[: int(0.9 * n_samples)]
y_train = y_digits[: int(0.9 * n_samples)]
X_test = X_digits[int(0.9 * n_samples) :]
y_test = y_digits[int(0.9 * n_samples) :]

knn = neighbors.KNeighborsClassifier()
logistic = linear_model.LogisticRegression(max_iter=1000)

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)
)