A Sequential Algorithm for Training Text Classifiers

Details A Sequential Algorithm for Training Text Classifiers A Sequential Algorithm for Training Text Classifiers

1994-07-24

arxiv.org/abs/cmp-lg/9407020v2

Computer Science

Computation and Language

10 pages, uuencoded, compressed PostScript; Proc. SIGIR-94 LaTex available from lewis@research.att.com

Scientific paper

The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual. An algorithm for sequential sampling during machine learning of statistical classifiers was developed and tested on a newswire text categorization task. This method, which we call uncertainty sampling, reduced by as much as 500-fold the amount of training data that would have to be manually classified to achieve a given level of effectiveness.

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