multi-label metric functions: precision, recall, f1 score

multi-label_metric_functions.py

def precision(y_true, y_pred):
    i = set(y_true).intersection(y_pred)
    len1 = len(y_pred)
    if len1 == 0:
        return 0
    else:
        return len(i) / len1

def recall(y_true, y_pred):
    i = set(y_true).intersection(y_pred)
    return len(i) / len(y_true)

def f1(y_true, y_pred):
    p = precision(y_true, y_pred)
    r = recall(y_true, y_pred)
    if p + r == 0:
        return 0
    else:
        return 2 * (p * r) / (p + r)

print(f1(['A', 'B', 'C'], ['A', 'B']))