Scikit-learn, get accuracy scores for each class

Question

Is there a built-in way for getting accuracy scores for each class separatetly? I know in sklearn we can get overall accuracy by using metric.accuracy_score. Is there a way to get the breakdown of accuracy scores for individual classes? Something similar to metrics.classification_report.

from sklearn.metrics import classification_report from sklearn.metrics import accuracy_score  y_true = [0, 1, 2, 2, 2] y_pred = [0, 0, 2, 2, 1] target_names = ['class 0', 'class 1', 'class 2'] 

classification_report does not give accuracy scores:

print(classification_report(y_true, y_pred, target_names=target_names, digits=4))  Out[9]:         precision    recall  f1-score   support  class 0     0.5000    1.0000    0.6667         1 class 1     0.0000    0.0000    0.0000         1 class 2     1.0000    0.6667    0.8000         3  avg / total     0.7000    0.6000    0.6133         5 

Accuracy score gives only the overall accuracy:

accuracy_score(y_true, y_pred) Out[10]: 0.59999999999999998 

Answer 1

from sklearn.metrics import confusion_matrix y_true = [2, 0, 2, 2, 0, 1] y_pred = [0, 0, 2, 2, 0, 2] matrix = confusion_matrix(y_true, y_pred) matrix.diagonal()/matrix.sum(axis=1)