Feature Importance with XGBClassifier

Question

Hopefully I\'m reading this wrong but in the XGBoost library documentation, there is note of extracting the feature importance attributes using feature_importances_

Answer 1

It seems like the api keeps on changing. For xgboost version 1.0.2, just changing from imp_vals = xgb.booster().get_fscore() to imp_vals = xgb.get_booster().get_fscore() in @David's answer does the trick. The updated code is -

from numpy import array

def get_xgb_imp(xgb, feat_names):
    imp_vals = xgb.get_booster().get_fscore()
    imp_dict = {feat_names[i]:float(imp_vals.get('f'+str(i),0.)) for i in range(len(feat_names))}
    total = array(imp_dict.values()).sum()
    return {k:v/total for k,v in imp_dict.items()}