Mining regression-classes in fuzzy point data sets

Authors:
Li-Li Wei
Affiliations:
School of Mathematics and Computer Science, Ningxia University, Yinchuan, P. R. China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
Year:
2009

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Abstract

Regression-class is defined as a subset of the data set that is subject to a regression mode. Mining regression-class in heterogeneous data sets is attracting much attention in a variety of disciplines. Traditional data sets can't reflect prior information of data. In this paper, we consider "fuzzy point data sets", which is defined by giving a fuzzy membership to the data in exact data sets, for helping us handle the confidence of data. We introduce regression-classes mixture decomposition method for mining regression classes in fuzzy point data sets. In the method, different regression-classes are mined sequentially in fuzzy point data sets. Numerical experiments show that by using fUzzy data point data, important data can make much contribution to regression-classes.