Journal
NEURAL COMPUTING & APPLICATIONS
Volume 25, Issue 6, Pages 1241-1247Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-014-1596-y
Keywords
SVM; TWSVM; Wavelet kernel function; WTWSVM
Categories
Funding
- National Natural Science Foundation of China [61379101]
- National Key Basic Research Program of China [2013CB329502]
Ask authors/readers for more resources
Twin support vector machine (TWSVM) is a research hot spot in the field of machine learning in recent years. Although its performance is better than traditional support vector machine (SVM), the kernel selection problem still affects the performance of TWSVM directly. Wavelet analysis has the characteristics of multivariate interpolation and sparse change, and it is suitable for the analysis of local signals and the detection of transient signals. The wavelet kernel function based on wavelet analysis can approximate any nonlinear functions. Based on the wavelet kernel features and the kernel function selection problem, wavelet twin support vector machine (WTWSVM) is proposed by this paper. It introduces the wavelet kernel function into TWSVM to make the combination of wavelet analysis techniques and TWSVM come true. The experimental results indicate that WTWSVM is feasible, and it improves the classification accuracy and generalization ability of TWSVM significantly.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available