ValueError：分类指标无法处理未知和多类目标的混合 site:stackoverflow.com 使用 classification_report() 时

Question

我正在尝试执行朴素贝叶斯模型并通过 classification_report() 显示结果 来自 sklearn

from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.feature_extraction.text import CountVectorizer

def multinomial(X_train, X_test, y_train, y_test):
  v = CountVectorizer( ngram_range = (2,3))
  #tfidf = TfidfVectorizer(stop_words = {'english'})
  
  model = MultinomialNB()
  X_train_set = v.fit_transform(X_train)
  X_test_set= v.transform(X_test)

  tf_transform = TfidfTransformer(use_idf=True).fit(X_train_set)
  X_train_tf = tf_transform.transform(X_train_set)
  X_test_tf = tf_transform.transform(X_test_set)
  X_train_tf
  y_train = y_train.astype('int')
  
  model.fit(X_train_tf, y_train )
  prediction = model.predict(X_test_tf)
  b_type = ["religion","age","ethnicity","gender","not bullying"]
  results = classification_report(y_test, prediction, target_names= b_type)
  print('Classification Report for Naive Bayes:\n',results)

multinomial(X_train, X_test, y_train, y_test)

运行上述代码时，出现如下错误结果，

ValueError                                Traceback (most recent call last)
<ipython-input-51-2d2045f2f956> in <module>
     23   print('Classification Report for Naive Bayes:\n',results)
     24 
---> 25 multinomial(X_train, X_test, y_train)

2 frames
<ipython-input-51-2d2045f2f956> in multinomial(X_train, X_test, y_train)
     20   prediction = model.predict(X_test_tf)
     21   b_type = ["religion","age","ethnicity","gender","not bullying"]
---> 22   results = classification_report(y_test, prediction)
     23   print('Classification Report for Naive Bayes:\n',results)
     24 

/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py in classification_report(y_true, y_pred, labels, target_names, sample_weight, digits, output_dict, zero_division)
   2108     """
   2109 
-> 2110     y_type, y_true, y_pred = _check_targets(y_true, y_pred)
   2111 
   2112     if labels is None:

/usr/local/lib/python3.8/dist-packages/sklearn/metrics/_classification.py in _check_targets(y_true, y_pred)
     91 
     92     if len(y_type) > 1:
---> 93         raise ValueError(
     94             "Classification metrics can't handle a mix of {0} and {1} targets".format(
     95                 type_true, type_pred

ValueError: Classification metrics can't handle a mix of unknown and multiclass targets

我不确定这个错误的确切原因是什么