CiteULike is a free online bibliography manager. Register and you can start organising your references online.

A comparative study on feature selection in text categorization Export

edited by: Douglas H. Fisher

In Proceedings of ICML-97, 14th International Conference on Machine Learning (1997), pp. 412-420.

Citation Format

[Posts]

View FullText article


ohkura's tags for this article

no-tag

X Reviews [Write a review of this article]

X Find related articles from these CiteULike users

X Find related articles with these CiteULike tags

X Posting History

X Abstract

This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), a Ø 2 -test (CHI), and term strength (TS). We found IG and CHI most effective in our experiments. Using IG thresholding with a knearest neighbor classifier on the Reuters corpus, removal of up to...


X BibTeX record

X RIS record


Privacy Statement | Terms & Conditions
CiteULike organises scholarly (or academic) papers or literature and provides bibliographic (which means it makes bibliographies) for universities and higher education establishments. It helps undergraduates and postgraduates. People studying for PhDs or in postdoctoral (postdoc) positions. The service is similar in scope to EndNote or RefWorks or any other reference manager like BibTeX, but it is a social bookmarking service for scientists and humanities researchers.