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

Answer 1

You can code it by yourself : the accuracy is nothing more than the ratio between the well classified samples (true positives and true negatives) and the total number of samples you have.

Then, for a given class, instead of considering all the samples, you only take into account those of your class.

You can then try this: Let's first define a handy function.

def indices(l, val):
   retval = []
   last = 0
   while val in l[last:]:
           i = l[last:].index(val)
           retval.append(last + i)
           last += i + 1   
   return retval

The function above will return the indices in the list l of a certain value val

def class_accuracy(y_pred, y_true, class):
    index = indices(l, class)
    y_pred, y_true = ypred[index], y_true[index]
    tp = [1 for k in range(len(y_pred)) if y_true[k]==y_pred[k]]
    tp = np.sum(tp)
    return tp/float(len(y_pred))

The last function will return the in-class accuracy that you look for.