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Knowledge Acquisition Tool for Learning Membership Function and Fuzzy Classification Rules from Numerical Data

by Fadl Mutaher Ba-alwi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 13
Year of Publication: 2013
Authors: Fadl Mutaher Ba-alwi
10.5120/10694-5603

Fadl Mutaher Ba-alwi . Knowledge Acquisition Tool for Learning Membership Function and Fuzzy Classification Rules from Numerical Data. International Journal of Computer Applications. 64, 13 ( February 2013), 24-30. DOI=10.5120/10694-5603

@article{ 10.5120/10694-5603,
author = { Fadl Mutaher Ba-alwi },
title = { Knowledge Acquisition Tool for Learning Membership Function and Fuzzy Classification Rules from Numerical Data },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 13 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 24-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number13/10694-5603/ },
doi = { 10.5120/10694-5603 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:17:03.883062+05:30
%A Fadl Mutaher Ba-alwi
%T Knowledge Acquisition Tool for Learning Membership Function and Fuzzy Classification Rules from Numerical Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 13
%P 24-30
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Generating suitable membership function (MF) is the core step of fuzzy classification system. This paper presents a novel learning algorithm that generates automatically reasonable MFs for quantitative attributes. In addition, a set of an appropriate fuzzy classification rules (FCRs) are discovered from a given numerical data. Each fuzzy rule (FR) is of the form IF-THEN rule. The antecedent IF-part and consequent THEN-part contain fuzzy sets. Since MFs are generated automatically, the proposed fuzzy learning algorithm can be viewed as a knowledge acquisition tool for classification problems. Experimental results on Iris dataset are presented to demonstrate the contribution of the proposed approach for generating MFs.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Classification Rule (FCR) knowledge acquisition tool Learning algorithm Membership function (MF)

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