Using support vector machines for time series prediction
Tài liệu tham khảo
Rius, 1998, Reliability of analytical systems: use of control charts, time series models and recurrent neural networks (RNN), Chemometrics and Intelligent Laboratory Systems, 40, 1, 10.1016/S0169-7439(97)00085-3
Burges, 1998, A tutorial on support vector machines for pattern recognition, Data Mining and Knowledge Discovery, 2, 121, 10.1023/A:1009715923555
A.J. Smola, B. Schölkopf, A tutorial on support vector regression, NeuroCOLT Technical Report NC-TR-98-030, Royal Holloway College, University of London, UK, 1998. Available on http://www.kernel-machines.org/
Müller, 1997, Predicting time series with support vector machines, 999
Belousov, 2002, A flexible classification approach with optimal generalisation performance: support vector machines, Chemometrics and Intelligent Laboratory Systems, 64, 15, 10.1016/S0169-7439(02)00046-1
Cristianini, 2000
Campbell, 2002, Kernel methods: a survey of current techniques, Neurocomputing, 48, 63, 10.1016/S0925-2312(01)00643-9
Schölkopf, 2002
Suykens, 2002
Krogh, 1995, A simple weight decay can improve generalization, vol. 4, 950
Box, 1976
Chatfield, 1980
Mandic, 2001
Mackey, 1977, Oscillation and chaos in physiological control systems, Science, 197, 287, 10.1126/science.267326
S.R. Gunn, Support vector machines for classification and regression, Technical report, Image speech and intelligent systems research group, University of Southampton, UK, 1997. Available on http://www.isis.ecs.soton.ac.uk/isystems/kernel/.
Mattera, 1999, Support vector machines for dynamic reconstruction of a chaotic system, 243
Platt, 1999, Flat training of support vector machines using sequential minimal optimisation, 185
Williams, 2001, Using the Nyström method to speed up kernel machines, vol. 13, 682
Fine, 2001, Efficient SVM training using low-rank kernel representation, Journal of Machine Learning Research, 2, 243
Joachims, 1999, Making large-scale support vector machines learning practical, 169
Suykens, 1999, Least squares support vector machines, Neural Processing Letters, 9, 293, 10.1023/A:1018628609742