W3School TIY Editor

from sklearn import datasets from sklearn.tree import DecisionTreeClassifier from sklearn.model_selection import KFold, cross_val_score # 加载鸢尾花数据集的特征和标签： X, y = datasets.load_iris(return_X_y=True) # 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) # 创建 5 折交叉验证器： k_folds = KFold(n_splits=5) # 执行交叉验证评估模型性能： scores = cross_val_score(clf, X, y, cv=k_folds) # 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))