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Iranian Journal of Optimization
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Volume Volume 10 (2018)
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mohammadi rad, M., afzali, M. (2018). Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring. Iranian Journal of Optimization, 10(1), 51-58.
majid mohammadi rad; mahdi afzali. "Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring". Iranian Journal of Optimization, 10, 1, 2018, 51-58.
mohammadi rad, M., afzali, M. (2018). 'Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring', Iranian Journal of Optimization, 10(1), pp. 51-58.
mohammadi rad, M., afzali, M. Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring. Iranian Journal of Optimization, 2018; 10(1): 51-58.

Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring

Article 6, Volume 10, Issue 1, Spring 2018, Page 51-58  XML PDF (7.78 MB)
Document Type: Research Paper
Authors
majid mohammadi rad 1; mahdi afzali2
1Department of Computer and Information Technology, Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2Faculty of Computer Engineering, Islamic Azad University, Zanjan Branch, Zanjan,Iran
Receive Date: 29 June 2017,  Revise Date: 30 August 2017,  Accept Date: 22 September 2017 
Abstract
In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank with the credit scoring approach. A survey was also used to measure the clustering validity index which resulted in a new validity index. Finally, the results were compared to identify the best algorithm and validity measure.
Keywords
Clustering; Data Mining; Evolution Algorithm; Credit Score, Clustering Validity Measure
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