Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Stability of continuous value discretisation: an application within rough set theory

Beynon, Malcolm James 2004. Stability of continuous value discretisation: an application within rough set theory. International Journal of Approximate Reasoning 35 (1) , pp. 29-53. 10.1016/S0888-613X(03)00057-4

Full text not available from this repository.

Abstract

Continuous value discretisation (CVD) is the process of partitioning a set of continuous values into a finite number of intervals (categories). This paper introduces a number of stability measures associated with the resultant CVD. The stability measures are constructed from a series of estimated probability distributions for the individual ‘partitioning’ intervals found using the method of Parzen windows. These measures enable comparisons between the results of alternative methods of CVD on their ability to effectively partition the continuous values. A further utilisation of these measures is exposited within rough set theory (RST). RST is a modern approach to the generation of sets of rules enabling the classification of objects to categories based on sets (reducts) of related characteristics. To avoid rules of poor quality (from RST analysis) induced directly from continuous valued characteristics, CVD methods can be used to reduce the associated granularity and allow higher rule quality. The notion of stability introduced enables the further introduction of novel measures particular to reduct and rule set stability within RST.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics
Uncontrolled Keywords: Data discretisation; Parzen windows; Stability; Rough set theory
Publisher: Elsevier
ISSN: 0888-613X
Last Modified: 04 Jun 2017 04:23
URI: http://orca.cf.ac.uk/id/eprint/37937

Citation Data

Cited 28 times in Google Scholar. View in Google Scholar

Cited 25 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item