F1-score per class for multi-class classification

Question

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

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

Is there something like that available on scikit-learn?

Answer 1

Taken from the f1_score docs.

from sklearn.metrics import f1_score
y_true = [0, 1, 2, 0, 1, 2]
y_pred = [0, 2, 1, 0, 0, 1]

f1_score(y_true, y_pred, average=None)

Ouputs:

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

Which is the scores for each class.