Prediction of Diabetes by Employing a New Data Mining Approach Which Balances Fitting and Generalization-Reference-Cited by-同舟云学术

Prediction of Diabetes by Employing a New Data Mining Approach Which Balances Fitting and Generalization

Published: Issue: Volume: Page:11-26
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Container-title:Computer and Information Science
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Author:

Pham Huy Nguyen Anh,Triantaphyllou Evangelos

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-79187-4_2.pdf

Reference13 articles.

1. Asuncion, A., Newman, D.J.: UCI-Machine Learning Repository. School of Information and Computer Sciences. University of California, Irvine, California, USA (2007)

2. Pham, H.N.A., Triantaphyllou, E.: The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining. In: Maimon, O., Rokach, L. (eds.) Soft Computing for Knowledge Discovery and Data Mining, Part 4, ch. 5, pp. 391–431. Springer, Heidelberg (2007)

3. Pham, H.N.A., Triantaphyllou, E.: An Optimization Approach for Improving Accuracy by Balancing Overfitting and Overgeneralization in Data Mining (January 2008) (submitted for publication)

4. American Diabetes Association (2007), http://www.diabetes.org/home.jsp

5. World Health Organization, Diabetes Mellitus: Report of a WHO Study Group. Geneva: WHO, Technical Report Series 727 (1985)

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