Title :
Genetic-Fuzzy Data Mining Techniques
Author :
Hong, Tzung-Pei ; Chen, Chun-Hao ; Tseng, Vincent S.
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
Abstract :
In this article, we have introduced some genetic-fuzzy data mining techniques and their classification. The concept of fuzzy sets is used to handle quantitative transactions and the process of genetic calculation is executed to find appropriate membership functions. The main contributions of this paper are that we first divided the genetic-fuzzy mining problems into four kinds according to the types of fuzzy mining problems and the ways of processing items. Then, each of the four kinds of problems has been described with some approaches given.
Keywords :
data mining; fuzzy set theory; genetic algorithms; genetic-fuzzy data mining; membership functions; Algorithm design and analysis; Association rules; Biological cells; Computer science; Electronic mail; Genetics; Data Miining; Fuzzy Data Mining; Fuzzy Set Theory; Genetic Algorithms; Genetic-Fuzzy Data Mining;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.157
