IP algorithms in compact rough classification modeling

The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. The algorithm is based on creating a 0-1 integer programming model from a rough discernibility relations of a decision system (DS) to find minimum selection of important attributes which is cal...

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Main Authors: Bakar, Azuraliza Abu, Sulaiman, Md Nasir, Othman, Mohamed, Selamat, Mohd Hasan
Format: Article
Language:English
Published: SAGE Publications 2001
Online Access:http://psasir.upm.edu.my/id/eprint/116064/
http://psasir.upm.edu.my/id/eprint/116064/1/116064.pdf
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author Bakar, Azuraliza Abu
Sulaiman, Md Nasir
Othman, Mohamed
Selamat, Mohd Hasan
author_facet Bakar, Azuraliza Abu
Sulaiman, Md Nasir
Othman, Mohamed
Selamat, Mohd Hasan
author_sort Bakar, Azuraliza Abu
building UPM Institutional Repository
collection Online Access
description The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. The algorithm is based on creating a 0-1 integer programming model from a rough discernibility relations of a decision system (DS) to find minimum selection of important attributes which is called reduct in rough set theory. A branch and bound search strategy that performs a non-chronological backtracking is proposed to solve the problem. The experimental result shows that the proposed IP algorithm has significantly reduced the number of rules generated from the obtained reducts with high percentage of classification accuracy. The branch and bound search strategy has shown reduction in certain amount of search.
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institution Universiti Putra Malaysia
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language English
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publishDate 2001
publisher SAGE Publications
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spelling upm-1160642025-03-19T03:44:05Z http://psasir.upm.edu.my/id/eprint/116064/ IP algorithms in compact rough classification modeling Bakar, Azuraliza Abu Sulaiman, Md Nasir Othman, Mohamed Selamat, Mohd Hasan The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. The algorithm is based on creating a 0-1 integer programming model from a rough discernibility relations of a decision system (DS) to find minimum selection of important attributes which is called reduct in rough set theory. A branch and bound search strategy that performs a non-chronological backtracking is proposed to solve the problem. The experimental result shows that the proposed IP algorithm has significantly reduced the number of rules generated from the obtained reducts with high percentage of classification accuracy. The branch and bound search strategy has shown reduction in certain amount of search. SAGE Publications 2001 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/116064/1/116064.pdf Bakar, Azuraliza Abu and Sulaiman, Md Nasir and Othman, Mohamed and Selamat, Mohd Hasan (2001) IP algorithms in compact rough classification modeling. Intelligent Data Analysis, 5 (5). pp. 419-429. ISSN 1571-4128; eISSN: 1088-467X https://journals.sagepub.com/doi/full/10.3233/IDA-2001-5505 10.3233/ida-2001-5505
spellingShingle Bakar, Azuraliza Abu
Sulaiman, Md Nasir
Othman, Mohamed
Selamat, Mohd Hasan
IP algorithms in compact rough classification modeling
title IP algorithms in compact rough classification modeling
title_full IP algorithms in compact rough classification modeling
title_fullStr IP algorithms in compact rough classification modeling
title_full_unstemmed IP algorithms in compact rough classification modeling
title_short IP algorithms in compact rough classification modeling
title_sort ip algorithms in compact rough classification modeling
url http://psasir.upm.edu.my/id/eprint/116064/
http://psasir.upm.edu.my/id/eprint/116064/
http://psasir.upm.edu.my/id/eprint/116064/
http://psasir.upm.edu.my/id/eprint/116064/1/116064.pdf