%0 Journal Article
%T An Efficient Smooth Quantile Boost  Algorithm for Binary Classification
%A Zhefeng Wang
%A Wanzhou Ye
%J Advances in Pure Mathematics
%P 615-624
%@ 2160-0384
%D 2016
%I Scientific Research Publishing
%R 10.4236/apm.2016.69050
%X In this paper, we propose a Smooth Quantile Boost Classification (SQBC) algorithm for binary classification problem. The SQBC algorithm directly uses a smooth function to approximate the ˇ°check functionˇ± of the quantile regression. Compared to other boost-based classification algorithms, the proposed algorithm is more accurate, flexible and robust to noisy predictors. Furthermore, the SQBC algorithm also can work well in high dimensional space. Extensive numerical experiments show that our proposed method has better performance on randomly simulations and real data.
%K Boosting
%K Quantile Regression
%K Smooth Check Function
%K Binary Classification
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=69990