HEDGES ALGEBRAS AND PROBLEM FUZZY PARTITION FOR QUALITATIVE ATTRIBUTES

Nguyen Tuan Anh, Trran Thai Son
Author affiliations

Authors

  • Nguyen Tuan Anh Đại học Công nghệ thông tin & Truyên thông - Đại học Thái Nguyên
  • Trran Thai Son

DOI:

https://doi.org/10.15625/1813-9663/32/4/9145

Keywords:

Data mining, fuzzy association rules, genetic algorithms, membership functions, Hedge algebras

Abstract

The pager refers to the construction of sets of the membership functions (MFs), which partition quantitative attributes in database into optimal fuzzy domains for extracting fuzzy association rules in the direction of hedge algebras approach. Some advantages of this method is demonstrated through the analysis of experiments on one set of standard data.

Keywords. Data mining; fuzzy association rules; genetic algorithms; membership functions; Hedge
algebras

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Published

21-08-2017

How to Cite

[1]
N. T. Anh and T. T. Son, “HEDGES ALGEBRAS AND PROBLEM FUZZY PARTITION FOR QUALITATIVE ATTRIBUTES”, JCC, vol. 32, no. 4, p. 335–350, Aug. 2017.

Issue

Section

Computer Science