W3School TIY Editor

from sklearn import datasets from sklearn.tree import DecisionTreeClassifier from sklearn.model_selection import LeaveOneOut, cross_val_score # 导入鸢尾花数据集的特征和标签： X, y = datasets.load_iris(return_X_y=True) # 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) # 创建留一法交叉验证对象： loo = LeaveOneOut() # 使用留一法进行交叉验证评估： scores = cross_val_score(clf, X, y, cv=loo) # 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))