Abstract
This paper describes ClaDia, a learning classifier system applied to the Wisconsin breast cancer data set, using a fuzzy representation of the rules, a median-based fuzzy combination rule, and separate subpopulations for each class. The system achieves a classification rate of over 90%, for many sets of system parameter values.
| Original language | English (US) |
|---|---|
| Pages | 1429-1435 |
| Number of pages | 7 |
| State | Published - 2000 |
| Event | Proceedings of the 2000 Congress on Evolutionary Computation - California, CA, USA Duration: Jul 16 2000 → Jul 19 2000 |
Other
| Other | Proceedings of the 2000 Congress on Evolutionary Computation |
|---|---|
| City | California, CA, USA |
| Period | 7/16/00 → 7/19/00 |
ASJC Scopus subject areas
- General Engineering
- General Computer Science
- Computational Theory and Mathematics