def sensitivity_score(y_true, y_pred, labels=None, pos_label=1, average='binary', sample_weight=None):
 (s, _, _) = sensitivity_specificity_support(y_true, y_pred, labels=labels, pos_label=pos_label, average=average, warn_for=('sensitivity',), sample_weight=sample_weight)
 return s

def sensitivity_score ( y_true , y_pred , labels = None , pos_label = 1 , average = 'binary' , sample_weight = None ) : ( s , _ , _ ) = sensitivity_specificity_support ( y_true , y_pred , labels = labels , pos_label = pos_label , average = average , warn_for = ( 'sensitivity' , ) , sample_weight = sample_weight ) return s
compute the sensitivity the sensitivity is the ratio tp / where tp is the number of true positives and fn the number of false negatives .