Your mileage will vary. It is often helpful to classify small parts of large articles and then somehow deal with these multiple classifications at the full document level.
Sometimes it is not helpful, especially if the small parts get too small. Try it both ways. My tendency is to prefer to classify book-sized things at a level smaller than a chapter and sometimes as small as a paragraph. Going below the paragraph level is usually bad. On Thu, Nov 1, 2012 at 3:23 AM, dennis zhuang <[email protected]> wrote: > Hi,all > > 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 can't find any documents about > this,can anybody help me?Thanks. > > -- > 庄晓丹 > Email: [email protected] [email protected] > Site: http://fnil.net > Twitter: @killme2008 >
