Subset selection using rough numeric dependency
Citation
Export citationSmith, T. C. & Holmes, G. (1995). Subset selection using rough numeric dependency. (Working paper 95/12). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
Permanent Research Commons link: https://hdl.handle.net/10289/1090
Abstract
In this paper we describe a novel method for performing feature subset selection for supervised learning tasks based on a refined notion of feature relevance. We define relevance as others see it and outline our refinement of this concept. We then describe how we use this new definition in an algorithm to perform subset selection, and finally, we show some preliminary results of using this approach with two quite different supervised learning schemes.
Date
1995-04Type
Report No.
95/12
Publisher
University of Waikato, Department of Computer Science
Collections
- 1995 Working Papers [32]