Title
A new feature selection method based on support vector machines for text categorization
Document Type
Article
Publication Title
International Journal of Data Analysis Techniques and Strategies
Abstract
As a machine intelligence paradigm, the support vector machines (SVMs) have tremendous potential for helping people to classify text document into a fixed number of predefined categories. The purpose of this paper is to discuss a new method of feature selection combined with principal component analysis and class profile-based feature as an input vector for SVMs classifier, and to demonstrate the effectiveness of this process. This paper also demonstrates that an applied method with SVMs improves categorisation performance and reduces the amount of time required to configure a learning machine. Copyright © 2011 Inderscience Enterprises Ltd.
First Page
1
Last Page
20
DOI
10.1504/IJDATS.2011.038803
Publication Date
1-1-2011
Recommended Citation
Xu, Yaquan and Wang, Haibo, "A new feature selection method based on support vector machines for text categorization" (2011). Business Faculty Publications. 126.
https://rio.tamiu.edu/arssb_facpubs/126