A hybrid feature selection method for credit scoring
نویسندگان
چکیده
منابع مشابه
A hybrid feature selection method for credit scoring
Reliable credit scoring models played a very important role of retail banks to evaluate credit applications and it has been widely studied. The main objective of this paper is to build a hybrid credit scoring model using feature selection approach. In this study, we constructed a credit scoring model based on parallel GBM (Gradient Boosted Model), filter and wrapper approaches to evaluate the a...
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The credit industry is a fast growing field, credit institutions collect data about credit customer and use them to build credit model. The collected information may be full of unwanted and redundant features which may speed down the learning process, so, effective feature selection methods are needed for credit dataset. In general, Filter feature selection methods outperform other feature sele...
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We address the problem of credit scoring as a classification and feature subset selection problem. Based on the current framework of sophisticated feature selection methods, we identify features that contain the most relevant information to distinguish good loan payers from bad loan payers. The feature selection methods are validated on several real world datasets with different types of classi...
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The performance of credit scoring models is determined by the used features. The relevant features for credit scoring usually are determined unsystematic and dominate by arbitrary trial. This paper presents a comparative study of four feature selection methods, which use data mining approach in reducing the feature space. The final results show that among the four feature selection methods, the...
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ژورنال
عنوان ژورنال: EAI Endorsed Transactions on Context-aware Systems and Applications
سال: 2017
ISSN: 2409-0026
DOI: 10.4108/eai.6-3-2017.152335