__init__.py 文件源码

def show_feature_importance(gbdt, feature_names=None):
    importance = gbdt.get_fscore(fmap='xgb.fmap')
    importance = sorted(importance.items(), key=operator.itemgetter(1))

    df = pd.DataFrame(importance, columns=['feature', 'fscore'])
    df['fscore'] = df['fscore'] / df['fscore'].sum()
    print "feature importance", df

    if feature_names is not None:
        used_features = df['feature']
        unused_features = [f for f in feature_names if f not in used_features]
        print "[IDF]Unused features:", str(unused_features)

    plt.figure()
    df.plot()
    df.plot(kind='barh', x='feature', y='fscore', legend=False, figsize=(6, 10))
    plt.title('XGBoost Feature Importance')
    plt.xlabel('relative importance')
    plt.gcf().savefig('feature_importance_xgb.png')