Facing this issue while predicting "CountVectorizer - Vocabulary wasn't fitted"

Question

#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 ?

Answer 1

You have to give your training set to the model to be trained

_= pipe.fit(triningSet.data, triningSet.target)

I don't see any training dataset here. you have to fit the CountVectoriser to your data set.