在光GBM documentation据说可以设置 predict_contrib=True
来预测 SHAP 值。
我们如何提取 SHAP 值(除了使用 shap
包)?
我试过了
model = LGBM(objective="binary",is_unbalance=True,predict_contrib=True)
model.fit(X_train,y_train)
pred_shap = opt_model.predict(X_train) #Does not get SHAP-values
这似乎不起作用
最佳答案
Shap 使用 pred_contrib=True
来评估 LGBM
方式:
from lightgbm.sklearn import LGBMClassifier
from sklearn.datasets import load_iris
X,y = load_iris(return_X_y=True)
lgbm = LGBMClassifier()
lgbm.fit(X,y)
lgbm_shap = lgbm.predict(X, pred_contrib=True)
# Shape of returned LGBM shap values: 4 features x 3 classes + 3 expected values over the training dataset
print(lgbm_shap.shape)
# 0th row of LGBM shap values for 0th feature
print(lgbm_shap[0,:4])
输出:
(150, 15)
[-0.0176954 0.50644615 5.56584344 3.43032313]
来自 shap
的形状值:
import shap
explainer = shap.TreeExplainer(lgbm)
shap_values = explainer.shap_values(X)
# num of predicted classes
print(len(shap_values))
# shap values for 0th class for 0th row
print(shap_values[0][0])
输出:
3
array([-0.0176954 , 0.50644615, 5.56584344, 3.43032313])
在我看来是一样的。
关于python - 在 LightGBM 中使用 'predict_contrib' 获取 SHAP 值,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/64783497/