基于sklearn,使用iris数据集前2列使用决策树进行预测,运行结果如下。试补全代码缺失部分。
时间: 2023-12-03 13:44:24 浏览: 23
```python
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# 加载数据集
iris = load_iris()
X = iris.data[:, :2] # 取前两列特征
y = iris.target
# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
# 定义决策树模型
clf = DecisionTreeClassifier()
# 训练模型
clf.fit(X_train, y_train)
# 预测测试集结果
y_pred = clf.predict(X_test)
# 计算准确率
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)
```
其中,缺失的代码部分为:
```python
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
```