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1Academic Journal
المؤلفون: 江彌修, 胡聚男, 黃立新, 陳靜怡, Chiang, Mi-hsiu, Hu, Chu-nan, Huang, Li-xin, Chen, Ching-yi
المساهمون: 金融系
مصطلحات موضوعية: 信用風險, 違約風險, 信用卡客戶, 集成學習, 機器學習, Credit risk, Default risk, Credit card clients, Ensemble learning, Machine learning
وصف الملف: 926314 bytes; application/pdf
Relation: 期貨與選擇權學刊, Vol.15, No.2, pp.71-119; https://nccur.lib.nccu.edu.tw//handle/140.119/135850; https://nccur.lib.nccu.edu.tw/bitstream/140.119/135850/1/133.pdf
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2Dissertation/ Thesis
المؤلفون: 陳靜怡, Chen, Ching-Yi
المساهمون: 江彌修, Chiang, Mi-Hsiu
مصطلحات موضوعية: 信用風險, 違約風險, 信用卡客戶, 集成學習, 機器學習, Credit risk, Default risk, Credit card clients, Ensemble learning, Machine learning, manag, eco
Relation: http://nccur.lib.nccu.edu.tw/bitstream/140.119/124140/1/201001.pdf; http://nccur.lib.nccu.edu.tw//handle/140.119/124140
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3Dissertation/ Thesis
المؤلفون: 陳靜怡, Chen, Ching-Yi
المساهمون: 江彌修, Chiang, Mi-Hsiu
مصطلحات موضوعية: 信用風險, 違約風險, 信用卡客戶, 集成學習, 機器學習, Credit risk, Default risk, Credit card clients, Ensemble learning, Machine learning
وصف الملف: 3744808 bytes; application/pdf
Relation: G0106352010; http://nccur.lib.nccu.edu.tw//handle/140.119/124140; http://nccur.lib.nccu.edu.tw/bitstream/140.119/124140/1/201001.pdf
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4Dissertation/ Thesis
المؤلفون: 陳靜怡, Chen, Ching-Yi
المساهمون: 江彌修, Chiang, Mi-Hsiu
مصطلحات موضوعية: 信用風險, 違約風險, 信用卡客戶, 集成學習, 機器學習, Credit risk, Default risk, Credit card clients, Ensemble learning, Machine learning
وصف الملف: 3744808 bytes; application/pdf
Relation: 中文文獻\n[1] 林萍珍、柯博昌、游俊忠 (2010)，演化式多重組合羅吉斯迴歸模型—應用於信用評等，資訊管理學報，第十七卷第二期，頁115-140。\n[2] 林榮禾，陳奕昌 (2008)，利用資料探勘技術建構整合型信用評等模型，國立臺北科技大學商業自動化與管理研究所碩士論文。\n[3] 柯柏成、孫玉清 (2014)，信用風險衡量模式之探討，證券櫃檯月刊170期，103年4月號，頁98-105。\n[4] 洪智力，陳勁宏 (2007)，破產預測選擇性集成模型比較，中原大學資訊管理學系會議論文。\n[5] 黃焜烽 (2018)，利用深度類神經網路模型預測台灣股價指數走勢，國立臺北大學金融與合作經營學系碩士論文。\n[6] 楊東翰 (2019)，深度校準：以G2++利率模型為例，國立政治大學金融研究所碩士論文。\n[7] 鍾經樊、黃嘉龍、黃博怡、謝有隆 (2006)，台灣地區企業信用評分系統的建置、驗證和比較，中央研究院經濟研究所。\n英文文獻\n[8] Barr, R.S., Helgason, R.V., Kennington, J.L., eds. (1997), Interfaces in Computer Science and Operations Research: Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies, Springer Publishing.\n[9] Desai, Y.S., Crook, J.N. & Overstreet, G.A. (1996), “A comparison of neural networks and linear scoring models in the credit environment,” European Journal of Operations Research, 85: 24–37.\n[10] Dietterich T.G. (2000), “Ensemble methods in machine learning,” Proceedings of the First International Workshop on Multiple Classifier Systems, pp. 1-15.\n[11] Sarkar, D., Natarajan, V. (2019), “Ensemble Machine Learning Cookbook: Over 35 practical recipes to explore ensemble machine learning techniques using Python,” PACKT Publishing, pp.188.\n[12] Foreman, R. D. (2003), “A Logistic Analysis of Bankruptcy within the US Local Telecommunications Industry,” Journal of Economics and Business, (55:2), pp. 135-166.\n[13] Koh, H.C., Tan, W.C., Goh, C.P. (2006), “A Two-step Method to Construct Credit Scoring Models with Data Mining Techniques,” International Journal of Business and Information, Volume 1, pp. 96-118.\n[14] He, H., Member, IEEE, and Edwardo A.G. (2009), “Learning from Imbalanced Data,” IEEE Transactions on Knowledge and Data Engineering, VOL. 21, NO. 9.\n[15] Ince, H., Aktan, B. (2008), “A comparison of data mining techniques for credit scoring in banking: A managerial perspective,” Journal of Business Economics and Management, 10(3): 233-240.\n[16] Yeh, I-C., Li, J.-W., Lee, Y.-S. & Ting, T.-M. (2010), “Can the Risk Probability of Credit Card Customers be Estimated?” Journal of Information Technology and Applications.\n[17] Kacprzyk, J., Pedrycz, W. (2015), Handbook of Computational Intelligence, Springer Publishing.\n[18] Kingma, D.T., Ba, J. (2014), “Adam: A Method For Stochastic Optimization,” arXiv:1412.6980[cs.LG].\n[19] Lo, A.W. (1986), “Logit Versus Discriminant Analysis-A Specification Test and Application to Corporate Bankruptcies,” Journal of Econometrics, Vol. 31, pp.151-178.\n[20] Ribeiro, M.T., Singh S. & Guestrin C. (2016), “Why Should I Trust You? Explaining the Predictions of Any Classifier,” KDD.\n[21] Ohlson, J. A. (1980), “Financial ratios and the probabilistic prediction of bankruptcy,” Journal of Accounting Research, 18, pp.109-131.\n[22] Peng, R.-Z. (2017), “Personal Credit Assessment Model Based on Stacking Ensemble Learning Algorithm,” Statistics and Application, 6(4), pp. 441-417.\n[23] Dzˇeroski, S., Zˇenko, B. (2004), “Is Combining Classifiers with Stacking Better than Selecting the Best One?” Kluwer Academic Publishers, pp.255-273.\n[24] West, D., Dellana, S & Qian, J. (2005), “Neural network ensemble strategies for financial decision applications,” Computers & Operations Research, Vol. 32, pp. 2543-2559.\n[25] Wolpert, D. (1992), “Stacked generalization,” Neural Networks, Volume 5, Issue 2, pp.241-259.\n[26] Tounsi, Y., Hassouni, L., & Anoun, H. (2018), “An Enhanced Comparative Assessment of Ensemble Learning for Credit Scoring,” International Journal of Machine Learning and Computing, Volume 8, No.5.; G0106352010; https://nccur.lib.nccu.edu.tw//handle/140.119/124140; https://nccur.lib.nccu.edu.tw/bitstream/140.119/124140/1/201001.pdf