1 |
M. W. Chang, Analysis of non stationary time series using support vector machines, www.kemel-machines.org
|
2 |
이광형, 오길록, Fuzzy 이론 및 응용 2권(응용), 홍릉과학출판사, 1997.
|
3 |
F. Alan, Stock Selection using Support Vector Machines, www.kernel-machines.org
|
4 |
C. W. Hsu, "A simple Decomposition Method for Support Vector Machines",Machine Learning, Vol. 46, pp. 291-314, 2002.
DOI
|
5 |
D. Yang, Provably Fast Training Algorithms for Support Vector Machines, http://www.kernel-machines.org
|
6 |
김대수, 신경망 이론과 응용(II), 하이테크 정보, 1993.
|
7 |
I. Takuya, "Fuzzy Support Vector Machines for Pattern Classification", www.kernel-machine.org
|
8 |
http://www.kernel-machines.org
|
9 |
C. F. Lin, "Fuzzy Support Vector Machines", IEEE Transactions on Neural Networks, Vol.13, No.2, March 2002.
|
10 |
J. T. Jeng, Support Vector Machines for the Fuzzy Neural Networks, http://kernel-machines.org
|
11 |
Z. Weida, "Linear programming support vector machines", J. Pattern Recognition Society, pp.1-10, 2001.
|
12 |
김대수, 신경망 이론과 응용(I), 하이테크정보, 1989.
|
13 |
이광형, 오길록, Fuzzy 이론 및 응용 1권(이론), 홍릉과학출판사, 1991.
|
14 |
D. Roobaert, Direct SVM : "A Simple Vector Machine Perceptron", J. of VLSI Signal Processing 32, pp. 147-156, 2002.
DOI
ScienceOn
|
15 |
N. Cristianini, An Introduction to Support Vector Machines, Cambridge University Press, 2000.
|
16 |
F. E. H. Tay, "Application of support vector machines in financial time series forecasting", Omega 29, pp. 309-317, 2002.
DOI
ScienceOn
|
17 |
D. Anguita, Fast Training of Support Vector Machines for Regression, http://www.kernel-machines.org
|
18 |
V. N. Vapnik, Statistical Learning Theory, Wiley-Interscience Pub., 1998.
|