Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data
- https://doi.org/10.2991/ifsa-eusflat-15.2015.67How to use a DOI?
- Fuzzy association rules, fuzzy rule base, reduction, coverage.
We present a technique for size reduction of a base of fuzzy association rules which is created using an automated approach and which is intended for inference. Our approach is based on controlling the coverage of training data by the rule base and removing only such rules that do not increase that coverage. Experiments show that such reduction is very effective while affecting the outputs of inference only very slightly.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Michal Burda AU - Martin Stepnicka PY - 2015/06 DA - 2015/06 TI - Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 463 EP - 470 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.67 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.67 ID - Burda2015/06 ER -