Facing Valueerror: Target Is Multiclass But Average='binary'

I'm a newbie to python as well as machine learning. As per my requirement, I'm trying to use Naive Bayes algorithm for my dataset. I'm able to find out the accuracy but trying to

Solution 1:

You need to add the 'average' param. According to the documentation:

average : string, [None, ‘binary’ (default), ‘micro’, ‘macro’, ‘samples’, ‘weighted’]

This parameter is required for multiclass/multilabel targets. If None, the scores for each class are returned. Otherwise, this determines the type of averaging performed on the data:

Do this:

print("Precision Score : ",precision_score(y_test, y_pred, 
                                           pos_label='positive'
                                           average='micro'))
print("Recall Score : ",recall_score(y_test, y_pred, 
                                           pos_label='positive'
                                           average='micro'))

Replace 'micro' with any one of the above options except 'binary'. Also, in the multiclass setting, there is no need to provide the 'pos_label' as it will be anyways ignored.

Update for comment:

Yes, they can be equal. Its given in the user guide here:

Note that for “micro”-averaging in a multiclass setting with all labels included will produce equal precision, recall and F, while “weighted” averaging may produce an F-score that is not between precision and recall.