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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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 HIGH-IMPACT PAPER 

Automatic Mining of Numerical Classification Rules with Parliamentary Optimization Algorithm

KIZILOLUK, S. See more information about KIZILOLUK, S. on SCOPUS See more information about KIZILOLUK, S. on IEEExplore See more information about KIZILOLUK, S. on Web of Science, ALATAS, B. See more information about ALATAS, B. on SCOPUS See more information about ALATAS, B. on SCOPUS See more information about ALATAS, B. on Web of Science
 
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Download PDF pdficon (1,850 KB) | Citation | Downloads: 950 | Views: 3,493

Author keywords
classification algorithms, computational intelligence, data mining, heuristic algorithms, optimization

References keywords
optimization(15), algorithm(7), science(5), parliamentary(5), mining(5), classification(5), rules(4), global(4), alatas(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-11-30
Volume 15, Issue 4, Year 2015, On page(s): 17 - 24
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.04003
Web of Science Accession Number: 000368499800003
SCOPUS ID: 84949980538

Abstract
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In recent years, classification rules mining has been one of the most important data mining tasks. In this study, one of the newest social-based metaheuristic methods, Parliamentary Optimization Algorithm (POA), is firstly used for automatically mining of comprehensible and accurate classification rules within datasets which have numerical attributes. Four different numerical datasets have been selected from UCI data warehouse and classification rules of high quality have been obtained. Furthermore, the results obtained from designed POA have been compared with the results obtained from four different popular classification rules mining algorithms used in WEKA. Although POA is very new and no applications in complex data mining problems have been performed, the results seem promising. The used objective function is very flexible and many different objectives can easily be added to. The intervals of the numerical attributes in the rules have been automatically found without any a priori process, as done in other classification rules mining algorithms, which causes the modification of datasets.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 12 [View]
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Cited-By SCOPUS

SCOPUS® Times Cited: 13
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Cited-By CrossRef

[1] RULE GENERATION BASED ON MODIFIED CUTTLEFISH ALGORITHM FOR INTRUSION DETECTION SYSTEM, EESA, Adel Sabry, SADIQ, Sheren, HASSAN, Masoud, ORMAN, Zeynep, Uludağ University Journal of The Faculty of Engineering, ISSN 2148-4147, 2021.
Digital Object Identifier: 10.17482/uumfd.747078
[CrossRef]

[2] Web Pages Classification with Parliamentary Optimization Algorithm, Kiziloluk, Soner, Ozer, Ahmet Bedri, International Journal of Software Engineering and Knowledge Engineering, ISSN 0218-1940, Issue 03, Volume 27, 2017.
Digital Object Identifier: 10.1142/S0218194017500188
[CrossRef]

[3] Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus, Singh, Namrata, Singh, Pradeep, Biocybernetics and Biomedical Engineering, ISSN 0208-5216, Issue 1, Volume 40, 2020.
Digital Object Identifier: 10.1016/j.bbe.2019.10.001
[CrossRef]

[4] New adaptive intelligent grey wolf optimizer based multi-objective quantitative classification rules mining approaches, Yildirim, Gungor, Alatas, Bilal, Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, Issue 10, Volume 12, 2021.
Digital Object Identifier: 10.1007/s12652-020-02701-9
[CrossRef]

[5] Socio-inspired evolutionary algorithms: a unified framework and survey, Sharma, Laxmikant, Chellapilla, Vasantha Lakshmi, Chellapilla, Patvardhan, Soft Computing, ISSN 1432-7643, Issue 19, Volume 27, 2023.
Digital Object Identifier: 10.1007/s00500-023-07929-z
[CrossRef]

[6] SM-RuleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification, Cheruku, Ramalingaswamy, Edla, Damodar Reddy, Kuppili, Venkatanareshbabu, Computers in Biology and Medicine, ISSN 0010-4825, Issue , 2017.
Digital Object Identifier: 10.1016/j.compbiomed.2016.12.009
[CrossRef]

[7] EEG Signal Classification for Concealed Information Test using Spider Monkey Candidate Rule Miner, M, Ramesh, Edla, Damodar Reddy, Multimedia Tools and Applications, ISSN 1573-7721, Issue 5, Volume 83, 2023.
Digital Object Identifier: 10.1007/s11042-023-16042-0
[CrossRef]

[8] AN IMPROVED ARTIFICIAL ATOM ALGORITHM WITH THE OPERATOR OF SHUFFLED FROG LEAPING ALGORITHM, ERDOĞAN YILDIRIM, Ayşe, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, ISSN 2149-0309, Issue 17, Volume 9, 2022.
Digital Object Identifier: 10.54365/adyumbd.1080995
[CrossRef]

[9] A novel hybrid GA–PSO framework for mining quantitative association rules, Moslehi, Fateme, Haeri, Abdorrahman, Martínez-Álvarez, Francisco, Soft Computing, ISSN 1432-7643, Issue 6, Volume 24, 2020.
Digital Object Identifier: 10.1007/s00500-019-04226-6
[CrossRef]

[10] Biogeography based optimization for mining rules to assess credit risk, Giri, Parimal Kumar, De, Sagar S., Dehuri, Sachidananda, Cho, Sung‐Bae, Intelligent Systems in Accounting, Finance and Management, ISSN 1055-615X, Issue 1, Volume 28, 2021.
Digital Object Identifier: 10.1002/isaf.1486
[CrossRef]

[11] Anlaşılabilir Sınıflandırma Kurallarının Ayçiçeği Optimizasyon Algoritması ile Otomatik Keşfi, YILDIRIM, Suna, YILDIRIM, Güngör, ALATAS, Bilal, Türk Doğa ve Fen Dergisi, ISSN 2149-6366, Issue 2, Volume 10, 2021.
Digital Object Identifier: 10.46810/tdfd.976397
[CrossRef]

[12] A new intelligent sunflower optimization based explainable artificial intelligence approach for early‐age concrete compressive strength classification and mixture design of RAC, Ulucan, Muhammed, Yildirim, Gungor, Alatas, Bilal, Alyamac, Kursat Esat, Structural Concrete, ISSN 1464-4177, Issue 6, Volume 24, 2023.
Digital Object Identifier: 10.1002/suco.202300138
[CrossRef]

[13] A Metaheuristic Perspective on Extracting Numeric Association Rules: Current Works, Applications, and Recommendations, Yacoubi, Salma, Manita, Ghaith, Chhabra, Amit, Korbaa, Ouajdi, Archives of Computational Methods in Engineering, ISSN 1134-3060, 2024.
Digital Object Identifier: 10.1007/s11831-024-10109-3
[CrossRef]

[14] ANT_FDCSM: A novel fuzzy rule miner derived from ant colony meta-heuristic for diagnosis of diabetic patients, Anuradha, , Singh, Akansha, Gupta, Gaurav, Journal of Intelligent & Fuzzy Systems, ISSN 1064-1246, Issue 1, Volume 36, 2019.
Digital Object Identifier: 10.3233/JIFS-172240
[CrossRef]

Updated 5 days, 13 hours ago

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