Text Categorization Test NLTK python
Just saving the model will not help. You should also save your VectorModel (like tfidfvectorizer or countvectorizer what ever you have used for fitting the train data). You can save those the same way using pickle. Also save all those models you used for pre-processing the train data like normalization/scaling models, etc. For the test data repeat the same steps by loading the pickle models that you saved and transform the test data in train data format that you used for model building and then you will be able to classify.
I have using nltk packages and train a model using Naive Bayes. I have save the model to a file using pickle package. Now i wonder how can i use this model to test like a random text not in the dataset and the model will tell if the sentence belong to which categorize?
Like my idea is i have a sentence : " Ronaldo have scored 2 goals against Egypt" And pass it to the model file and return categorize "sport".