政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/30872
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 92416/122720 (75%)
Visitors : 26254756      Online Users : 120
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/30872

    Title: 資料採礦技術在保險公司客戶保單貸款行為研究的應用
    Authors: 邱蔚群
    Lilian Chiu
    Contributors: 鄭宇庭
    Lilian Chiu
    Keywords: 資料採礦
    Date: 2002
    Issue Date: 2009-09-14
    Abstract: 摘 要


    In the past, the analysis of insurance data is usually conducted with traditional statistical methods, however a large amount of valuable information hidden might be left undiscovered.
    The purpose of this research is to apply data mining techniques to customer policy data taken from one of insurance company’s database in Kaoshuing city and county to study the behavior of customers taking loans against their policies as a reference for insurance company in promoting policy in the future.
    From the cleansed data, we sample policies of different sizes and percentage of policies with loans by different sampling methods, decision trees and neural network models, then through the significant interactions of ANOVA, discuss how the results being influenced by the four factors. We then choose the best model that manifests factors affecting customer’s behavior in taking out the loan thus providing insurance company a vital information in targeting its customers group.
    Reference: 參考文獻
    l Berry, M. J. A., and Linoff, G. S. (1997), Data Mining Techniques: for Marketing, Sales, and Customer Support. John Wiley & Sons Inc, New York.
    l Berry, M. J. A., and Linoff, G. S. (2000), Mastering Data Mining Techniques, The Art & Science of Customer Relationship Management. John Wiley & Sons Inc., New York.
    l Breiman, L. Friedman, J.H., Olshen, R. A., and Stone, C. J. (1984).. Classification and Regression Trees. Wadsworth, Pacific Grove, California.
    l Dunham, M. H. (2003), Data Mining: Introductory and Advanced Topics. Pearson Education Inc., Upper Saddle River, New Jersey.
    l Freund, Y., and Schapire, R. E. (1996), “Experiments with a New Boosting Algorithm”. Machine Learning: Proceedings of the Thirteenth International Conference.
    l Friedman, J., Hastie, T., and Tibshirani R. (1998), Additive Logistic Regression: a Statistical View of Boosting,
    l Smith, M. (1993), Neural Networks for Statistical Modeling. Van Norstrand Reinhold, New York.
    l Terano, T., Liu, H., and Chen, A. L. P. (2000), Knowledge Discovery and Data Mining: Current Issues and New Applications. Springer-Verlag, Berling, Germany.
    l Witten, I. H., and Eibe, F. (2000), Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers, San Francisco, California.
    l 中國科學技術大學生物醫學工程跨係委員會,神經網路及其應用,儒林圖書,1993。
    l 呂奇傑,演化式類神經網路分類技術於資料探勘上之應用,輔大應統所碩士論文,2000。
    l 張維哲,人工神經網路,全欣資訊圖書,1992。
    l 陳智宏,應用類神經網路於電力系統負載之溫度敏感度分析,中山電機工程所碩士論文,2001。
    l 黃國源,類神經網路與圖形辨識,維科,2000。
    l 葉怡成,類神經網路模式應用與實作(第7版),儒林圖書公司,台北市,2000。
    l 傅心家,神經網路導論,第三波,1991。
    l 楊雅媛,迴歸分析與類神經網路預測能力之比較,政大統計所碩士論文,2002。
    l 鄭忠樑,運用分類樹於股價報酬率預測之研究,元智大學資訊管理研究所碩士論文,民國九十一年。
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0090354004
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

    Files in This Item:

    File SizeFormat

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback