trainning.py 文件源码

def get_graph_features_mean(col_list):

    am = analyse_mean.set_index('features')
    am = am.stack().reset_index()
    am.columns = ['features', 'type', 'score']
    plt.figure(figsize=(18,6));

    if isinstance(bench_features_bool, list):
        print "List"
        sns.barplot('score', 'features', data=am[am.features.isin(col_list)], hue='type', hue_order=['error','good'])
    else:
        sns.barplot('score', 'features', data=am[am.features == col_list], hue='type', hue_order=['error','good'])

#    plt.xticks(rotation=40)
    plt.legend()

# base :                                                                                                # 0.9412 ***
# without : u'is_mister_word_1b', u'is_mister_word_2b', u'is_mister_word_1a', u'is_mister_word_2a'      # 0.9344
# without : word_encoded'                                                                               # 0.9268