Abstract
Support Vector Machine has some advantages, such as simple structure and good generalization, which is one implementation in Statistical Learning Theory. SVM offers a kind of effective way for the data fusion problem of little sample, non-linear and high dimension. In this paper, mobile agents are applied to data fusion system. The model and the study method of data fusion system are improved. An approach of data fusion based on SVM is proposed. The experiment results show that this hierarchical and parallel SVM training algorithm is efficient to deal with large-scale classification problems and has more satisfying accuracy in classification precision.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.