regression - 如何在XGBoost回归器中找到模型系数？

Question

在XGBoost回归中预测价格，如何获取系数，模型的截距？像我们在Statsmodel中获得线性回归一样，如何获取模型摘要？
见下面的代码

from xgboost import XGBRegressor

# fit model no training data
model = XGBRegressor()
model.fit(X_train, y_train)

# make predictions for test data
y_pred = model.predict(X_test)

print("R^2: {}".format(model.score(X_test, y_test)))
rmse = np.sqrt(mean_squared_error(y_test, y_pred))
print("Root Mean Squared Error: {}".format(rmse))

这就是我建立模型并尝试获得这样的系数的方式:

#print the intercept
print(model.intercept_)

AttributeError: Intercept (bias) is not defined for Booster type gbtree

print(model.coef_)

AttributeError: Coefficients are not defined for Booster type gbtree

有人可以帮我解决这个问题吗？谢谢。

Answer 1

xgboost reference note on coef_ property:

Coefficients are only defined when the linear model is chosen as base learner (booster=gblinear). It is not defined for other base learner types, such as tree learners (booster=gbtree).

默认值为booster = gbtree