Seyed Sadatrasoul

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This paper presents a comprehensive review of the studies conducted in the application of data mining techniques focus on credit scoring from 2000 to 2012. Yet, there isn‟t adequate literature reviews in the field of data mining applications in credit scoring. Using a novel research approach, this paper investigates academic and systematic literature review(More)
Credit scoring is an important topic and banks collect different data from their loan applicants to make appropriate and correct decisions. Rule bases are favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants. This paper, uses four feature selection approaches as features pre-processing(More)
Credit scoring is an important topic, and banks collect different data from their loan applicant to make an appropriate and correct decision. Rule bases are of more attention in credit decision making because of their ability to explicitly distinguish between good and bad applicants. The credit scoring datasets are usually imbalanced. This is mainly because(More)
Credit scoring is a classification problem leading to introducing numeroustechniques to deal with itsuch as support vector machines, neural networks and rule-based classifiers. Rule bases are the top priority in credit decision making because of their ability to explicitly distinguish between good and bad applicants. In a creditscoring context, imbalanced(More)
Credit allocation through the usage of Portfolio optimization mainly seeks to maximize return and minimize the risk of the portfolio; but there are other important issues including sustainable development which is important for government/public sectors. This paper presents a novel credit allocation approach based on portfolio optimization and investigates(More)
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