I have built binary text classifier using SVM on TF-IDF for news articles(Sports: Non-Sports).
But I not sure how to classify new document using this model. Since TF-IDF is calculated based on the occurrence of a word in all other documents.
Do I have merge test and train data every time I receive a new document for classification? It will change the model as well every time.
Am I missing something? I think, although SVM on TF-IDF giving good results it can not be used in production.
Is there any other way to tackle this issue?