Measures of Rule Quality for Feature Selection in Text Categorization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

Elena Montañés , Javier Fernández , Irene Díaz , Elías F. Combarro , José Ranilla

ABSTRACT

Text Categorization is the process of assigning documents to a set of previously fixed categories. A lot of research is going on with the goal of automating this time-consuming task. Several different algorithms have been applied, and Support Vector Machines have shown very good results. In this paper we propose a new family of measures taken from the Machine Learning environment to apply them to feature reduction task. The experiments are performed on two different corpus (Reuters and Ohsumed). The results show that the new family of measures performs better than the traditional Information Theory measures. More... »

PAGES

589-598

References to SciGraph publications

Book

TITLE

Advances in Intelligent Data Analysis V

ISBN

978-3-540-40813-0
978-3-540-45231-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-45231-7_54

DOI

http://dx.doi.org/10.1007/978-3-540-45231-7_54

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004356335


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