#these are classifier and  vectorizer

vectorizer = CountVectorizer(tokenizer = spacy_tokenizer, ngram_range=(1,1))
classifier = LinearSVC()

I have created a Pipeline as shown below

# Create the  pipeline to clean, tokenize, vectorize, and classify
pipe = Pipeline([("cleaner", predictors()),
                 ('vectorizer', vectorizer),
                  ('classifier', classifier)])

while predicting the test dataset, im facing this issue.

sample_prediction = pipe.predict(X_test)

ERROR : sklearn.exceptions.NotFittedError: CountVectorizer - Vocabulary wasn't fitted.

Can anyone help ?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.