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Authors
Affiliations
1 Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
2 Kohgiluyeh and Boyer Ahmad Science and Research Branch, Islamic Azad University, Iran
Source
Indian Journal of Science and Technology, Vol 9, No 7 (2016), Pagination:
Abstract
Background/Objectives: Insurance data analysis can be considered as a way of losses reduction by using data mining. It uses the machine learning, pattern recognition and data base theory for discovering the unknown knowledge. Methods/Statistical Analysis: In this paper, information of 2011, third party insurance of Iran insurance company auto has analyzed in Kohgiluyeh and Boyer Ahmad by using the data mining method. Findings: The results show that using clustering algorithms with acceptable clusters will be able to provide a model to identify affecting factors and to determine the effect of them in the profit and loss of auto third party insurance. Applications/Improvements: The algorithm of K-Means has formed the best clustering with 9 clusters that have relatively good quality. It means that has been able to maximize the distance between the cluster and minimize the within cluster distance.
Keywords
Clustering Algorithm, Data Mining, Insurance, Profit and Loss, Third Party
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