Data mining application in banking sector with clustering and classification methods
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Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Because of the phenomenal rise in information, future forecasting systems about strategy development were needed in each area. Therefore, data mining techniques are used extensively in banking area such as many areas. In this study, conducted in banking sector, it was aimed to reduce the rate of risk in decision making to a minimum via analysis of existing personal loan customers and estimate potential customers' payment performances with k-means method is one of the clustering techniques and the decision trees method which is one of the models of classification in data mining. In the study, SPSS Clementine was used as a software of data mining and an application was done for evaluation of personal loan customers. © 2015 IEEE.
Açıklama
5th International Conference on Industrial Engineering and Operations Management, IEOM 2015, 3 March 2015 through 5 March 2015,
Anahtar Kelimeler
Classification, Clustering, Data Mining, Personal Loans, Spss Clementine
Kaynak
IEOM 2015 - 5th International Conference on Industrial Engineering and Operations Management, Proceeding
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Çalış, A., Boyacı, A., Baynal, K. (2015, March). Data mining application in banking sector with clustering and classification methods. 2015 International Conference on Industrial Engineering and Operations Management (IEOM), Dubai, United Arab Emirates.
