當使用XGB想得到特徵重要性時報錯，程式碼及報錯如下，

model = XGBRegressor(
    learning_rate = 0.1,
    n_estimators = 300,
    max_depth = 7,
    min_child_weight = 3,
    subsample = 0.8,
    colsample_bytree = 0.8,
    seed = 0
)

model.fit( X_train, y_train, eval_metric='mae',
    eval_set=[(X_train, y_train), (X_valid, y_valid)],
    early_stopping_rounds=20 )
y_pred = model.predict( X_valid )

feat_imp = pd.Series(model.booster().get_fscore())
feat_imp = feat_imp.sort_values( ascending=False )
feat_imp[:10].plot( kind='bar', title='Feature Importances' )
plt.ylabel( 'Feature Importance Score' )
plt.show()
 

 遇到這個問題，開始我是佷懵的。

參考https://stackoverflow.com/questions/38212649/feature-importance-with-xgbclassifier上的內容後找到解決方法。

 此時我們只需要將model.booster()改為model.get_booster()即可。