每类F1分数，可进行多类别分类 [英] F1-score per class for multi-class classification

问题描述

我正在使用python和scikit-learn处理多类分类问题.目前，我正在使用classification_report函数评估分类器的性能，并获得如下报告:

I'm working on a multiclass classification problem using python and scikit-learn. Currently, I'm using the classification_report function to evaluate the performance of my classifier, obtaining reports like the following:

>>> print(classification_report(y_true, y_pred, target_names=target_names))
             precision    recall  f1-score   support

    class 0       0.50      1.00      0.67         1
    class 1       0.00      0.00      0.00         1
    class 2       1.00      0.67      0.80         3

avg / total       0.70      0.60      0.61         5

要进行进一步的分析，我对获得每个可用班级的每班级f1分数很感兴趣.也许是这样的:

To do further analysis, I'm interesting in obtaining the per-class f1 score of each of the classes available. Maybe something like this:

>>> print(calculate_f1_score(y_true, y_pred, target_class='class 0'))
0.67

在scikit-learn上有类似的内容吗?

Is there something like that available on scikit-learn?

推荐答案

来自f1_score 胜利:

array([ 0.8,  0. ,  0. ])

每个班的分数是多少.

这篇关于每类F1分数，可进行多类别分类的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！