导入所需的包

from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn.metrics import accuracy_score

将数据集划分为训练集和测试集

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)

构建决策树分类器

clf = DecisionTreeClassifier(random_state=42)

在训练集上训练模型

clf.fit(X_train, y_train)

在测试集上预测

y_pred = clf.predict(X_test)

计算模型的准确率

accuracy = accuracy_score(y_test, y_pred) print("模型的准确率为：", accuracy)