precision recall f1-score support 0 0.92 0.92 0.92 10762 1 0.85 0.92 0.89 9339 2 0.86 0.45 0.59 1628 micro avg 0.88 0.88 0.88 21729 macro avg 0.88 0.76 0.80 21729 weighted avg 0.88 0.88 0.88 21729 samples avg 0.88 0.88 0.88 21729是reportsreports_dict = [] for report in reports: lines = report.strip().split('\n') classifier_name = lines[0].strip() data = {} for line in lines[2:]: category, precision, recall, f1_score, support = line.strip().split()中for line in lines[2:]: category, precision, recall, f1_score, support = line.strip().split()出现oo many values to unpack (expected 5) on line weighted avg 0.88 0.88 0.88 21729 Error: too many values to unpack (expected 5) on line samples avg 0.88 0.88 0.88 21729怎么修正

可以将代码修改为以下形式，使用 *args 解包任意数量的参数，并将前4个参数赋值给相应的变量，最后一个参数用于支持度的计数，可以忽略。

for line in lines[2:]:
    category, *scores, support = line.strip().split()
    precision, recall, f1_score = map(float, scores)

这样就能够正确地解包出前4个参数并将其赋值给相应的变量了。