W3School TIY Editor

from sklearn import datasets

from sklearn.tree import DecisionTreeClassifier

from sklearn.model_selection import LeaveOneOut, cross_val_score

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# 导入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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# 初始化决策树分类器，固定随机种子保证结果可重复：

clf = DecisionTreeClassifier(random_state=42)

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# 创建留一法交叉验证对象：

loo = LeaveOneOut()

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# 使用留一法进行交叉验证评估：

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

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# 输出验证结果：

print("交叉验证得分：", scores)

print("平均交叉验证得分：", scores.mean())

print("参与平均的交叉验证次数：", len(scores))