> I am using sgd classifier for our articles classification.I want to > train a new model,but there is a problem.I can provide the learner a large > article or some small articles, but i extract only one vector for one > article.Then i don't know is there any difference between one vector and > many vectors for learner when training? Should i provide the learner one > large article or many small articles?
i'm not sure i understand your question, but i guess you're saying that each article is a separate training example? in terms of differing lengths you might want to try some different normalisation approaches but i'd try without anything first. http://nlp.stanford.edu/IR-book/html/htmledition/variant-tf-idf-functions-1.html is a good place to start mat
