Comparing Linear Discriminant Analysis and Support Vector Machines
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[1] J. Mercer. Functions of positive and negative type, and their connection with the theory of integral equations , 1909 .
[2] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[3] Keinosuke Fukunaga,et al. Introduction to statistical pattern recognition (2nd ed.) , 1990 .
[4] G. McLachlan. Discriminant Analysis and Statistical Pattern Recognition , 1992 .
[5] Keinosuke Fukunaga,et al. Statistical Pattern Recognition , 1993, Handbook of Pattern Recognition and Computer Vision.
[6] Jerome H. Friedman,et al. Flexible Metric Nearest Neighbor Classification , 1994 .
[7] Robert Tibshirani,et al. Discriminant Adaptive Nearest Neighbor Classification , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[8] J. C. BurgesChristopher. A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .
[9] Thorsten Joachims,et al. Making large scale SVM learning practical , 1998 .
[10] Alexander J. Smola,et al. Learning with kernels , 1998 .
[11] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[12] B. Schölkopf,et al. Advances in kernel methods: support vector learning , 1999 .
[13] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[14] Colin Campbell,et al. Bayes Point Machines , 2001, J. Mach. Learn. Res..
[15] Michael I. Jordan,et al. Kernel independent component analysis , 2003 .