Experimentally optimal ν in support vector regression for different noise models and parameter settings
- 1 January 2004
- journal article
- research article
- Published by Elsevier in Neural Networks
- Vol. 17 (1) , 127-141
- https://doi.org/10.1016/s0893-6080(03)00209-0
Abstract
No abstract availableKeywords
This publication has 3 references indexed in Scilit:
- New Support Vector AlgorithmsNeural Computation, 2000
- Asymptotically Optimal Choice of ε-Loss for Support Vector MachinesPublished by Springer Nature ,1998
- Network information criterion-determining the number of hidden units for an artificial neural network modelIEEE Transactions on Neural Networks, 1994