def recall_score(y_real, y_pred):
 (_, r, _) = precision_recall_fscore(y_real, y_pred)
 return np.average(r)

def recall_score ( y_real , y_pred ) : ( _ , r , _ ) = precision_recall_fscore ( y_real , y_pred ) return np . average ( r )
compute the recall the recall is the ratio tp / where tp is the number of true positives and fn the number of false negatives .