-
2
-
-
84901569634
-
Laplace kernel with automatic smoothing parameter estimation for support vector machine
-
Ali, S. & Smith, K.A. (2004a). Laplace kernel with automatic smoothing parameter estimation for support vector machine. Computational Management Science (submitted).
-
(2004)
Computational Management Science (submitted)
-
-
Ali, S.1
Smith, K.A.2
-
3
-
-
85001711518
-
Automatic kernel selection for support vector machines
-
Ali, S. & Smith, K.A. (2004b). Automatic kernel selection for support vector machines. Neurocomputing (submitted).
-
(2004)
Neurocomputing (submitted)
-
-
Ali, S.1
Smith, K.A.2
-
4
-
-
0032786569
-
Improving support vector machine classifiers by modifying kernel functions
-
Amari, S.-I. & Wu, S. (1999). Improving support vector machine classifiers by modifying kernel functions. Neural Networks, 12, 783–789.
-
(1999)
Neural Networks
, vol.12
, pp. 783-789
-
-
Amari, S.-I.1
Wu, S.2
-
5
-
-
0033333598
-
On support vector decision trees for database marketing
-
Bennett, K.P., Wu, S., & Auslender, L. (1999). On support vector decision trees for database marketing. In Proceedings of the IEEE International Joint Conference on Neural Networks, IJCNN'99 (pp. 904–909).
-
(1999)
In Proceedings of the IEEE International Joint Conference on Neural Networks, IJCNN'99
, pp. 904-909
-
-
Bennett, K.P.1
Wu, S.2
Auslender, L.3
-
7
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
Boser, B.E., Guyon, I., & Vapnik, V.N. (1992). A training algorithm for optimal margin classifiers. In Proceedings of the Fifth Annual Workshop of Computational Learning Theory, Pittsburgh, Pennsylvania (pp. 144–152).
-
(1992)
In Proceedings of the Fifth Annual Workshop of Computational Learning Theory, Pittsburgh, Pennsylvania
, pp. 144-152
-
-
Boser, B.E.1
Guyon, I.2
Vapnik, V.N.3
-
8
-
-
1642276856
-
A meta-learning method to select the kernel width in support vector regression
-
Carlos, S., Pavel, B., & Brazdil, P. (2004). A meta-learning method to select the kernel width in support vector regression. Machine Learning, 54, 195–209.
-
(2004)
Machine Learning
, vol.54
, pp. 195-209
-
-
Carlos, S.1
Pavel, B.2
Brazdil, P.3
-
9
-
-
0036161011
-
Choosing multiple parameters for support vector machines
-
Chapelle, O., Vapnik, V., Bousquet, O., & Mukherjee, S. (2002). Choosing multiple parameters for support vector machines. Machine Learning, 46(1), 131–159.
-
(2002)
Machine Learning
, vol.46
, Issue.1
, pp. 131-159
-
-
Chapelle, O.1
Vapnik, V.2
Bousquet, O.3
Mukherjee, S.4
-
10
-
-
34249753618
-
Support vector networks
-
Cortes C. & Vapnik, V. (1995). Support vector networks. Machine Learning, 20, 273–297.
-
(1995)
Machine Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
11
-
-
0030145401
-
A note on comparing classifier
-
Duin, R.P.W. (1996). A note on comparing classifier. Pattern Recognition Letters, 1, 529–536.
-
(1996)
Pattern Recognition Letters
, vol.1
, pp. 529-536
-
-
Duin, R.P.W.1
-
12
-
-
0034419669
-
Regularization networks and support vector machines
-
Evgeniou, T., Pontil, M., & Poggio, T. (2000). Regularization networks and support vector machines. Advances in Computational Mathematics, 13(1), 1–50.
-
(2000)
Advances in Computational Mathematics
, vol.13
, Issue.1
, pp. 1-50
-
-
Evgeniou, T.1
Pontil, M.2
Poggio, T.3
-
15
-
-
0036161259
-
Gene selection for cancer classification using support vector machines
-
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine Learning, 46(1/3), 389–422.
-
(2002)
Machine Learning
, vol.46
, Issue.1-3
, pp. 389-422
-
-
Guyon, I.1
Weston, J.2
Barnhill, S.3
Vapnik, V.4
-
17
-
-
10044232174
-
Pattern classification using support vector machine ensemble
-
Hyun-Chul, K., Shaoning, P., Hong-Mo, J., Daijin, K., & Sung-Yang, B. (2002). Pattern classification using support vector machine ensemble. In Proceedings of the IEEE 16th International Conference on Pattern Recognition (pp. 160–163).
-
(2002)
In Proceedings of the IEEE 16th International Conference on Pattern Recognition
, pp. 160-163
-
-
Hyun-Chul, K.1
Shaoning, P.2
Hong-Mo, J.3
Daijin, K.4
Sung-Yang, B.5
-
19
-
-
0032251894
-
Convergence properties of the Nelder-Mead simplex method in low dimensions
-
Lagarias, J.C., Reeds, J.A., Wright, M.H., & Wright, P.E. (1998). Convergence properties of the Nelder-Mead simplex method in low dimensions. SIAM Journal of Optimisation, 9, 112–147.
-
(1998)
SIAM Journal of Optimisation
, vol.9
, pp. 112-147
-
-
Lagarias, J.C.1
Reeds, J.A.2
Wright, M.H.3
Wright, P.E.4
-
23
-
-
0035272287
-
An introduction to kernel-based learning algorithms
-
Muller, K.-R., Mika, S., Ratsch, G., Tsuda, K., & Scholkopf, B. (2001). An introduction to kernel-based learning algorithms. IEEE Transactions on Neural Networks, 12(2), 181–201.
-
(2001)
IEEE Transactions on Neural Networks
, vol.12
, Issue.2
, pp. 181-201
-
-
Muller, K.-R.1
Mika, S.2
Ratsch, G.3
Tsuda, K.4
Scholkopf, B.5
-
24
-
-
0036085407
-
Experimental analysis of support vector machines with different kernels based on non-intrusive monitoring data
-
Onoda, T., Murata, H., Ratsch, G., & Muller, K.-R. (2002). Experimental analysis of support vector machines with different kernels based on non-intrusive monitoring data. In Proceedings of the IEEE International Joint Conference on Neural Networks (pp. 2186–2191).
-
(2002)
In Proceedings of the IEEE International Joint Conference on Neural Networks
, pp. 2186-2191
-
-
Onoda, T.1
Murata, H.2
Ratsch, G.3
Muller, K.-R.4
-
25
-
-
0242576444
-
Expediting model selection for support vector machines based on data reduction
-
Ou, Y.-Y., Chen, C.-Y., Hwang, S.-C., & Oyang, Y.-J. (2003). Expediting model selection for support vector machines based on data reduction. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (pp. 786–791).
-
(2003)
In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
, pp. 786-791
-
-
Ou, Y.-Y.1
Chen, C.-Y.2
Hwang, S.-C.3
Oyang, Y.-J.4
-
26
-
-
10044249849
-
SVM classification using sequences of phonemes and syllables
-
Paab, G., Leopold, E., Larson, M., Kindermann, J., & Eickeler, S. (2002). SVM classification using sequences of phonemes and syllables. In Proceedings of the European Conference on Machine Learning, ECML, Helsinki.
-
(2002)
In Proceedings of the European Conference on Machine Learning, ECML, Helsinki
-
-
Paab, G.1
Leopold, E.2
Larson, M.3
Kindermann, J.4
Eickeler, S.5
-
27
-
-
0037411308
-
Growing support vector classifiers with controlled complexity
-
Parrado-Hernandez, E., Mora-Jimenez, I., Arenas-Garca, J., Figueiras-Vidal, A.R., & Navia-Vazquez, A. (2003). Growing support vector classifiers with controlled complexity. Pattern Recognition, 36, 1479–1488.
-
(2003)
Pattern Recognition
, vol.36
, pp. 1479-1488
-
-
Parrado-Hernandez, E.1
Mora-Jimenez, I.2
Arenas-Garca, J.3
Figueiras-Vidal, A.R.4
Navia-Vazquez, A.5
-
31
-
-
30344451274
-
Modelling the relationship between problem characteristics and data mining algorithm performance using neural networks
-
In C. Dagli et al. (Eds.) ASME Press
-
Smith, K.A., Woo, F., Ciesielski, V., & Ibrahim, R. (2001). Modelling the relationship between problem characteristics and data mining algorithm performance using neural networks. In C. Dagli et al. (Eds.), Smart engineering system design: Neural networks, fuzzy logic, evolutionary programming, data mining, and complex systems (pp. 357–362). ASME Press.
-
(2001)
Smart engineering system design: Neural networks, fuzzy logic, evolutionary programming, data mining, and complex systems
, pp. 357-362
-
-
Smith, K.A.1
Woo, F.2
Ciesielski, V.3
Ibrahim, R.4
-
32
-
-
30344479028
-
Matching data mining algorithm suitability to data characteristics using a self-organising map
-
In A. Abraham & M. Koppen (Eds.) Heidelberg: Physica-Verlag
-
Smith, K.A., Woo, F., Ciesielski, V., & Ibrahim, R. (2002). Matching data mining algorithm suitability to data characteristics using a self-organising map. In A. Abraham & M. Koppen (Eds.), Hybrid information systems (pp. 169–180). Heidelberg: Physica-Verlag.
-
(2002)
Hybrid information systems
, pp. 169-180
-
-
Smith, K.A.1
Woo, F.2
Ciesielski, V.3
Ibrahim, R.4
-
35
-
-
0036298128
-
Evaluation of kernel methods for speaker verification and identification
-
Wan, V. & Renals, S. (2002). Evaluation of kernel methods for speaker verification and identification. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'02, (pp. 669–672).
-
(2002)
In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'02
, pp. 669-672
-
-
Wan, V.1
Renals, S.2
|