- author = "M. H. Marghny and I. E. El-Semman",
- title = "Extracting fuzzy classification rules with gene expression programming",
- booktitle = "CGST International Conference on Artificial Intelligence and Machine Learning (AIML-05)",
- year = "2005",
- editor = "H. Elmahdy",
- pages = "17--22",
- address = "Cairo, Egypt",
- month = "19-21 " # dec,
- keywords = "genetic algorithms, genetic programming, Gene Expression Programming, data mining, fuzzy classification rules, logic operators",
-
URL = "
http://www.icgst.com/paper.aspx?pid=P1120535114",
-
URL = "
http://www.icgst.com/AIML05/papers/P1120535114.pdf",
- size = "6 pages",
- abstract = "In essence, data mining consists of extracting knowledge from data. This paper proposes an evolutionary system for discovering fuzzy classification rules. Fuzzy logic is useful for data mining especially in the case for performing classification task. Three methods were used to extract fuzzy classification rules using Evolutionary Algorithms: (1) genetic selection small number of large number of fuzzy candidate rules, (2) genetic reduction of genetic space, selection fuzzy rules from large the candidate rules, (3) genetic learning of fuzzy classification rules. In this paper, we propose a new gene expression programming (GEP) algorithm for discovering logical fuzzy classification rules, the proposed method has been tested and the results are comparable with other techniques include Genetic Programming (GP)",
-
notes = "Title etc. updated Dec
2022
http://www.icgst.com/AIML05/conference/index.html aiml2005@icgst.com
P1120535114.pdf format odd, perhaps try alternative PDF viewers.
Dept. of Computer Science, Faculty of Computers and Information, Assuit University, Egypt",
