用python写一段随机森林分类代码

以下是用Python编写的随机森林分类代码：

# 导入必要的库
from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split

# 生成随机数据集
X, y = make_classification(n_samples=1000, n_features=4, random_state=0, shuffle=False)

# 将数据集拆分为训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)

# 创建随机森林分类器对象
clf = RandomForestClassifier(n_estimators=100, max_depth=2, random_state=0)

# 训练模型
clf.fit(X_train, y_train)

# 预测测试集
y_pred = clf.predict(X_test)

# 输出模型得分
print(clf.score(X_test, y_test))

希望这段代码对你有所帮助！