Multiclass Least Squares Auto-Correlation Wavelet Support Vector Machines

Authors:
Yongzhong Xing;Xiaobei Wu;Zhiliang Xu
Affiliations:
-;-;-
Venue:
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
Year:
2008

Citing 0
Cited 1

Hybrid model based on wavelet support vector machine and modified genetic algorithm penalizing Gaussian noises for power load forecasts

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, combining the auto-correlation wavelet kernel with multiclass least squares support vector machine (MLS-SVM), a novel notion of multiclass least squares support vector machine with universal auto-correlation wavelet kernels (MLSAWSVM) is proposed. The translation invariant property of the kernel function enhances the generalization ability of the LS-SVM method and the spiral multiclass classification experimental results show some advantages of MLS-AWSVM over MLSSVM on the classification and the generalization performance.