如何在Python语言中获得RandomForest模型的准确性？

from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split

# 假设X为特征数据，y为目标变量
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 创建RandomForest模型
model = RandomForestClassifier()

# 在训练集上拟合模型
model.fit(X_train, y_train)

# 在测试集上进行预测
y_pred = model.predict(X_test)

# 计算准确性
accuracy = accuracy_score(y_test, y_pred)
print("RandomForest模型的准确性：", accuracy)