Title : ( A GA-based Fuzzy Mining Algorithm Using Selections Pressure Technique For Extracting Membership Functions )
Authors: zohreh davarzani , Mahnaz Kadkhoda , Mohammad Reza Akbarzadeh Totonchi ,
Full TextAbstract
Extracting association rules from transaction data is one of the most important purposes of data mining. In this paper, an enhanced Genetic- Fuzzy algorithm to derive membership functions dynamically from quantitative transaction data has been proposed. In this approach, selection pressure technique is used to adjust membership functions and fuzzify transaction data. Some experiments are also made to compare the proposed algorithm and existing approach. The results showed that the efficiency of proposed algorithm is better than the existing one.
Keywords
, Data Mining, Membership Function, Association Rule, Genetic Algorithm, Fuzzy Set.
@inproceedings{paperid:1016186,
author = {Davarzani, Zohreh and Kadkhoda, Mahnaz and Akbarzadeh Totonchi, Mohammad Reza},
title = {A GA-based Fuzzy Mining Algorithm Using Selections Pressure Technique For Extracting Membership Functions},
booktitle = {3rp joint congress on fuzzy and intelligent systems},
year = {2009},
location = {یزد, IRAN},
keywords = {Data Mining; Membership Function; Association Rule; Genetic Algorithm; Fuzzy Set.},
}
%0 Conference Proceedings
%T A GA-based Fuzzy Mining Algorithm Using Selections Pressure Technique For Extracting Membership Functions
%A Davarzani, Zohreh
%A Kadkhoda, Mahnaz
%A Akbarzadeh Totonchi, Mohammad Reza
%J 3rp joint congress on fuzzy and intelligent systems
%D 2009
