Enhanced Algorithm Performance for Classification Based on Hyper Surface using Bagging and Adaboost

@article{He2007EnhancedAP,
  title={Enhanced Algorithm Performance for Classification Based on Hyper Surface using Bagging and Adaboost},
  author={Qing He and F Zhuang and Xiu-Rong Zhao and Zhong-Zhi Shi},
  journal={2007 International Conference on Machine Learning and Cybernetics},
  year={2007},
  volume={6},
  pages={3624-3629}
}
To improve the generality ability of Hyper Surface Classification (HSC) , Bagging and AdaBoost ensemble learning methods are proposed in this paper. HSC is a covering learning algorithm, in which a model of hyper surface is obtained by adaptively dividing the sample space and then the hyper surface is directly used to classify large database based on Jordan Curve Theorem in Topology. Experiments results confirm that Bagging and AdaBoost can improve the generality ability of Hyper Surface… CONTINUE READING