Subset selection using rough numeric dependency
Smith, 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
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.
University of Waikato, Department of Computer Science
- 1995 Working Papers