Text analysis for unstructured data
The Naive Bayes classifier is a supervised learning method and requires you to train it using labelled data in which you know the targets in advance. You can then use it on unlabelled data to predict future values but you can't train it on data with no target values.
It's hard to recommend a different method without knowing more about your task but it sounds like you want to look into unsupervised clustering algorithms. k-means is a relatively simple one to start with.
I have a Question 
i do have large amount of Unstructured  text data , which i want to classify into different -different sectors .
i am using a Naive Bayes classifier for it 
Now, my question is what should i pass in Y?? because i don't have a Target values 
and as per the syntax i have to pass it .
mnb = MultinomialNB()
mnb.fit(X,y)
TypeError: fit() missing 1 required positional argument: 'y'
As i said i don't have target value.
How can i do that?
Help will be appreciated