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220855

MEMETIC PROGRAMMING WITH THE ATOMIC REPRESENTATION FOR EXTRACTING LOGICAL CLASSIFICATION RULES

Article

Last updated: 28 Dec 2024

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Tags

Mathematics and Computer Science

Abstract

Classification is one of the most popular techniques of data mining. This paper presents an evolutionary approach for designing classifiers for two-class classification problems using an enhanced version of the genetic programming (GP) algorithm, called the Memetic  Programming  (MP)  algorithm. MP can discover relationships between observed data and express them logically. MP aims to obtain a classifier with the largest area under the ROC curve, which has been proved a better performance than traditionally metrics. The proposed approach is being demonstrated by experimenting on some UCI Machine Learning data sets. Results obtained in these experiments reflect the efficiency of the proposed algorithm.

DOI

10.21608/aunj.2020.220855

Keywords

classification, Evolutionary Algorithm, Local Search Procedure, Memetic Programming, ROC Curves

Volume

49

Article Issue

1

Related Issue

31477

Issue Date

2020-06-01

Receive Date

2022-02-21

Publish Date

2020-06-01

Page Start

1

Page End

17

Print ISSN

2812-5029

Online ISSN

2812-5037

Article File

AUNJ_Volume 49_Issue 1_Pages 1-17.pdf

PDF . 817.4kB

Link

https://aunj.journals.ekb.eg/article_220855.html

Detail API

https://aunj.journals.ekb.eg/service?article_code=220855

Order

220,855

Type

Novel Research Articles

Type Code

2,242

Publication Type

Journal

Publication Title

Assiut University Journal of Multidisciplinary Scientific Research

Publication Link

https://aunj.journals.ekb.eg/

MainTitle

MEMETIC PROGRAMMING WITH THE ATOMIC REPRESENTATION FOR EXTRACTING LOGICAL CLASSIFICATION RULES

Details

Type

Article

Created At

23 Jan 2023