Scikit-learn, get accuracy scores for each class
<p>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 <code>metric.accuracy_score</code>. Is there a way to get the breakdown of accuracy scores for individual classes? Something similar to <code>metrics.classification_report</code>.</p>

<pre><code>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']
</code></pre>

<p><code>classification_report</code> does not give accuracy scores:</p>

<pre><code>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
</code></pre>

<p>Accuracy score gives only the overall accuracy:</p>

<pre><code>accuracy_score(y_true, y_pred)
Out[10]: 0.59999999999999998
</code></pre>