W3School TIY Editor

from sklearn import datasets

from sklearn.tree import DecisionTreeClassifier

from sklearn.model_selection import KFold, cross_val_score

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# 加载鸢尾花数据集的特征和标签：

X, y = datasets.load_iris(return_X_y=True)

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# 创建决策树分类器，设置随机种子确保结果可复现：

clf = DecisionTreeClassifier(random_state=42)

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# 创建 5 折交叉验证器：

k_folds = KFold(n_splits=5)

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# 执行交叉验证评估模型性能：

scores = cross_val_score(clf, X, y, cv=k_folds)

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# 输出交叉验证结果：

print("交叉验证得分：", scores)

print("平均交叉验证得分：", scores.mean())

print("用于计算平均得分的验证次数：", len(scores))