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--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[18], line 2 1 feature_df = pd.DataFrame(X.toarray(), ----> 2 ...

The error message you encountered indicates that the ‘CountVectorizer’ object does not have the attribute ‘get_feature_names’.

In scikit-learn, the ‘get_feature_names()’ method is typically used with the ‘CountVectorizer’ or ‘TfidfVectorizer’ objects to retrieve the feature names after fitting and transforming the data.

To resolve this issue, you can try the following steps:

  1. Verify that you have imported the necessary libraries correctly, including pandas and sklearn.
  2. Check if you have initialized your CountVectorizer object as CV_binary = CountVectorizer(...). Make sure it is properly initialized.
  3. Confirm that you have fit-transformed your data using X = CV_binary.fit_transform(data).
  4. Ensure that there are actual features extracted from your text data by printing out X.shape or examining its contents.
  5. If step 4 shows valid features, try accessing them using CV_binary.get_feature_names_out() instead of CV_binary.get_feature_names(). This change is introduced in newer versions of scikit-learn.

By following these suggestions, you should be able to access the feature names without encountering the ‘AttributeError’.


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