A novel approach for the hyperparameters of support vector regression

Proceedings of the International Joint Conference on Neural Networks

Volumn 1, Issue , 2002, Pages 642-647

  Jeng, Jing Tsong ^a   Chuang, Chen Chia ^a  

^a HWA HSIA INSTITUTE OF TECHNOLOGY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; FUNCTION EVALUATION; OPTIMIZATION; PARAMETER ESTIMATION; REGRESSION ANALYSIS; VECTOR QUANTIZATION;

COMPETITIVE AGGLOMERATION CLUSTERING ALGORITHM; INSENSITIVE LOSS FUNCTION; OPTIMUM HYPERPARAMETERS; SUPPORT VECTOR REGRESSION;

LEARNING ALGORITHMS;

EID: 0036076598     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Optimal control by least squares support vector machines
2. Nonlinear prediction of chaotic time series using a support vector machine
3. A tutorial on support vector regression
4. Support vector method for function approximation, regression estimation, and signal processing
5. General cost functions for support vector regression
6. Interval regression analysis with support vector regression networks
7. Support vector machine for annealing robust fuzzy neural network with outlier
8. Annealing robust radial basis function networks for modeling with outliers
9. Application of support vector machines in financial time series forecasting
10. Choosing kernel parameters for support vector machines
11. Clustering by competitive agglomeration
12. A robust competitive clustering algorithm with applications in computer vision