A flexible classification approach with optimal generalisation performance: support vector machines
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[1] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[2] Wei-Yin Loh,et al. A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms , 2000, Machine Learning.
[3] Christopher J. C. Burges,et al. A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.
[4] A. Belousov,et al. Applicational aspects of support vector machines , 2002 .
[5] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[6] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[7] Nello Cristianini,et al. Support vector machine classification and validation of cancer tissue samples using microarray expression data , 2000, Bioinform..
[8] Nello Cristianini,et al. An introduction to Support Vector Machines , 2000 .
[9] D Haussler,et al. Knowledge-based analysis of microarray gene expression data by using support vector machines. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[10] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[11] Sarunas Raudys. How good are support vector machines? , 2000, Neural Networks.
[12] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[13] Robert P. W. Duin,et al. Support vector domain description , 1999, Pattern Recognit. Lett..
[14] Robert P. W. Duin,et al. Pump Failure Detection Using Support Vector Data Descriptions , 1999, IDA.
[15] Jill P. Mesirov,et al. Computational Biology , 2018, Encyclopedia of Parallel Computing.
[16] B. Schölkopf,et al. Advances in kernel methods: support vector learning , 1999 .
[17] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[18] S. D. Jong,et al. Handbook of Chemometrics and Qualimetrics , 1998 .
[19] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[20] Johanna Smeyers-Verbeke,et al. Handbook of Chemometrics and Qualimetrics: Part A , 1997 .
[21] Bernhard Schölkopf,et al. Support vector learning , 1997 .
[22] Desire L. Massart,et al. Comparison of regularized discriminant analysis linear discriminant analysis and quadratic discriminant analysis applied to NIR data , 1996 .
[23] Christopher M. Bishop,et al. Modelling conditional probability distributions for periodic variables , 1995 .
[24] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[25] Danny Coomans,et al. Improvements to the classification performance of RDA , 1993 .
[26] Anil K. Jain,et al. Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[27] L. N. Kanal,et al. Uncertainty in Artificial Intelligence 5 , 1990 .
[28] J. Friedman. Regularized Discriminant Analysis , 1989 .
[29] Desire L. Massart,et al. Evaluation of the required sample size in some supervised pattern recognition techniques , 1989 .
[30] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[31] Keinosuke Fukunaga,et al. Introduction to Statistical Pattern Recognition , 1972 .