Research on SVM ensemble and its application to remote sensing classification

Heng-nian Qi, Mei-li Huang
2007 Proceedings on Intelligent Systems and Knowledge Engineering (ISKE2007)   unpublished
The paper analyzes the key concepts, theories and methods of machine learning ensemble, and reviews the related studies on support vector machine (SVM) ensemble. The experiments on the remote sensing classification show that SVM ensemble is more accurate than single SVM. To obtain an effective SVM ensemble, we propose a selective SVM ensemble approach based on fuzzy clustering and discuss the issues on it.
doi:10.2991/iske.2007.102 fatcat:dfk6nbqzyvgljjcilooc5lr7gy