Facing ValueError: Target is multiclass but average=’binary’

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.