12.8 文献笔记
12.8 文献笔记¶
支持向量机背后的理论归功于 Vapnik 并且在 Vapnik (1996)1 中进行了描述。有关 SVM 的新兴文献、由 Alex Smola 和 Bernhard Scholkopf 创造并维护的在线文献，可以在下面的网站中找到
http://www.kernel-machines.org/
我们的处理是基于 Wahba et al. (2000)2 和 Evgeniou et al. (2000)3，以及Burges (Burges, 1998)4 的教程。
线性判别分析归功于 Fisher (1936)5 和 Rao (1973)6。其与最优得分的联系至少可以追溯到 Breiman and Ihaka (1984)7，以及 Fisher (1936)8 中的一种简单形式。其与对应分析 (Greenacre, 1984)9有很强的关联。灵活的、带惩罚的以及混合判别分析的描述是取自 Hastie et al. (1994)10, Hastie et al. (1995)11 以及 Hastie and Tibshirani (1996b)12, Hastie et al. (1998)13 对这三者进行了总结；也可以参见 Ripley (1996)14。
- 1
Vapnik, V. (1996). The Nature of Statistical Learning Theory, Springer, New York.
- 2
Wahba, G., Lin, Y. and Zhang, H. (2000). GACV for support vector machines, in A. Smola, P. Bartlett, B. Sch¨olkopf and D. Schuurmans (eds), Advances in Large Margin Classifiers, MIT Press, Cambridge, MA., pp. 297–311.
- 3
Evgeniou, T., Pontil, M. and Poggio, T. (2000). Regularization networks and support vector machines, Advances in Computational Mathematics 13(1): 1–50.
- 4
Burges, C. (1998). A tutorial on support vector machines for pattern recognition, Knowledge Discovery and Data Mining 2(2): 121–167.
- 5
Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems, Eugen. 7: 179–188.
- 6
Rao, C. R. (1973). Linear Statistical Inference and Its Applications, Wiley, New York.
- 7
Breiman, L. and Ihaka, R. (1984). Nonlinear discriminant analysis via scaling and ACE, Technical report, University of California, Berkeley.
- 8
Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems, Eugen. 7: 179–188.
- 9
Greenacre, M. (1984). Theory and Applications of Correspondence Analysis, Academic Press, New York.
- 10
Hastie, T., Tibshirani, R. and Buja, A. (1994). Flexible discriminant analysis by optimal scoring, Journal of the American Statistical Association 89: 1255–1270.
- 11
Hastie, T., Buja, A. and Tibshirani, R. (1995). Penalized discriminant analysis, Annals of Statistics 23: 73–102.
- 12
Hastie, T. and Tibshirani, R. (1996b). Discriminant analysis by Gaussian mixtures, Journal of the Royal Statistical Society Series B. 58: 155–176.
- 13
Hastie, T. and Tibshirani, R. (1998). Classification by pairwise coupling, Annals of Statistics 26(2): 451–471.
- 14
Ripley, B. D. (1996). Pattern Recognition and Neural Networks, Cambridge University Press.