用sklean实现knn手写数字识别

使用sklearn库实现KNN手写数字识别的步骤如下：

1. 导入所需的库和数据集：

from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier

2. 加载手写数字数据集：

digits = load_digits()
X = digits.data
y = digits.target

3. 划分训练集和测试集：

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

4. 创建KNN分类器并进行训练：

knn = KNeighborsClassifier(n_neighbors=5)
knn.fit(X_train, y_train)

5. 进行预测：

y_pred = knn.predict(X_test)

6. 评估模型性能：

accuracy = knn.score(X_test, y_test)
print("准确率：", accuracy)