Title :
Multiclass Least Squares Auto-Correlation Wavelet Support Vector Machines
Author :
Xing, Yongzhong ; Wu, Xiaobei ; Xu, Zhiliang
Author_Institution :
Nanjing Univ. of Sci. & Technol., Nanjing
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 (MLS- AWSVM) 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 MLS- SVM on the classification and the generalization performance.
Keywords :
generalisation (artificial intelligence); least squares approximations; support vector machines; wavelet transforms; generalization ability; kernel function; multiclass least squares auto-correlation wavelet support vector machines; translation invariant property; Autocorrelation; Information analysis; Kernel; Least squares methods; Signal processing; Spirals; Support vector machine classification; Support vector machines; Wavelet analysis; Wavelet transforms;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.375