我有用于多类文本分类的训练模型代码，并且它运行正常，但我无法使用该模型。这是我的训练代码

def training(df):
    X = df.Text
    y = df.Tags
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
    lr = Pipeline([('vect', CountVectorizer()),
                   ('tfidf', TfidfTransformer()),
                   ('clf', LogisticRegression()),
                   ])
    lr.fit(X_train, y_train)
    y_pred1 = lr.predict(X_test)
    print(f"Accuracy is : {accuracy_score(y_pred1, y_test)}")
    print(lr.predict('ماست کم چرب 900 گرمی رامک'))

当我运行代码时，得到了这样的结果 Accuracy is : 0.9957983193277311 以及以下错误

• Traceback (most recent call last):File “E:\Python\NLP Project\Beta_00\Level0\handleClassification.py”, line 100, in training(df)

  File “E:\Python\NLP Project\Beta_00\Level0\handleClassification.py”, line 85, in trainingprint(lr.predict(‘ماست کم چرب 900 گرمی رامک’))

  File “E:\Python\NLP Project\Beta_00\venv\lib\site-packages\sklearn\utils\metaestimators.py”line 120, in out = lambda *args, **kwargs: self.fn(obj, *args, **kwargs)

  File “E:\Python\NLP Project\Beta_00\venv\lib\site-packages\sklearn\pipeline.py”, line 418, inpredictXt = transform.transform(Xt)

  File “E:\Python\NLP Project\Beta_00\venv\lib\site-
  packages\sklearn\feature_extraction\text.py”, line 1248, in transformraise ValueError(ValueError: Iterable over raw text documents expected, string object received.

回答：

以下几行需要更正:

lr.fit(X_train, y_train)
y_pred1 = lr.predict(X_test)
print(f"Accuracy is : {accuracy_score(y_test, y_pred1)}")   #<--- 这里
print(lr.predict(['ماست کم چرب 900 گرمی رامک']))   #<--- 这里

行 lr.predict(input) 应该接收 ‘array’ 类型的输入。