A VNS-EDA Algorithm-Based Feature Selection for Credit Risk Classification
المؤلفون المشاركون
Li, Zhongfei
Chen, Wei
Guo, Jinchao
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-04-27
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Many quantitative credit scoring models have been developed for credit risk assessment.
Irrelevant and redundant features may deteriorate the performance of credit risk classification.
Feature selection with metaheuristic techniques can be applied to excavate the most significant features.
However, metaheuristic techniques suffer from various issues such as being trapped in local optimum and premature convergence.
Therefore, in this article, a hybrid variable neighborhood search and estimation of distribution technique with the elitist population strategy is proposed to identify the optimal feature subset.
Variable neighborhood search with the elitist population strategy is used to direct its local searching in order to optimize the ergodicity, avoid premature convergence, and jump out of the local optimum in the searching process.
The probabilistic model attempts to capture the probability distribution of the promising solutions which are biased towards the global optimum.
The proposed technique has been tested on both publicly available credit datasets and a real-world credit dataset in China.
Experimental analysis demonstrates that it outperforms existing techniques in large-scale credit datasets with high dimensionality, making it well suited for feature selection in credit risk classification.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Wei& Li, Zhongfei& Guo, Jinchao. 2020. A VNS-EDA Algorithm-Based Feature Selection for Credit Risk Classification. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1195217
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Wei…[et al.]. A VNS-EDA Algorithm-Based Feature Selection for Credit Risk Classification. Mathematical Problems in Engineering No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1195217
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Wei& Li, Zhongfei& Guo, Jinchao. A VNS-EDA Algorithm-Based Feature Selection for Credit Risk Classification. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1195217
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1195217
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر