XGBoost feature_importances_ 参数返回 nan

Question

我有以下代码xgb = XGBRegressor(booster='gblinear', reg_lambda=0, learning_rate=0.028) print(xgb)xgb.fit(X_train_sc, y_train)y_pred = xgb.predict(X_test_sc)print("\nFeature Importances:")for item in zip(feature_list_transform, xgb.feature_importances_):    print("{1:10.4f} - {0}".format(item[0],item[1]))print("\nR-squared, training set:")print(xgb.score(X_train_sc,y_train))print("R-squared, test set:")print(xgb.score(X_test_sc,y_test))print("\nRoot-mean squared error, from metrics:")mse = mean_squared_error(y_test, y_pred)rmse = np.sqrt(mse)print(rmse)输出是：    XGBRegressor(base_score=0.5, booster='gblinear', colsample_bylevel=1,           colsample_bytree=1, gamma=0, learning_rate=0.028, max_delta_step=0,           max_depth=3, min_child_weight=1, missing=None, n_estimators=100,           n_jobs=1, nthread=None, objective='reg:linear', random_state=0,           reg_alpha=0, reg_lambda=0, scale_pos_weight=1, seed=None,           silent=True, subsample=1)    Feature Importances:           nan - fertility_rate_log           nan - life_expectancy_log           nan - avg_supply_of_protein_of_animal_origin_log           nan - access_to_improved_sanitation_log           nan - access_to_improved_water_sources_log           nan - obesity_prevalence_log           nan - open_defecation_log           nan - access_to_electricity_log           nan - cereal_yield_log           nan - population_growth_log           nan - avg_value_of_food_production_log           nan - gross_domestic_product_per_capita_ppp_log           nan - net_oda_received_percent_gni_log           nan - adult_literacy_rate           nan - school_enrollment_rate_female           nan - school_enrollment_rate_total           nan - caloric_energy_from_cereals_roots_tubers           nan - anemia_prevalence           nan - political_stability和错误：c:\python36\lib\site-packages\xgboost\sklearn.py:420: RuntimeWarning: 在 true_divide 中遇到无效值 return all_features / all_features.sum()如何修复这个nan并获得系数？最后，该模型运行良好。