A Robust Formulation For Support Vector Regression

CIS WORKSHOPS 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY WORKSHOPS（2007）

引用 0|浏览0

暂无评分

摘要

This paper investigates a new support vector regression model in which the observed data are corrupted with noise. We present a second-order cone programming formulation for designing robust regression which can handle uncertainty in data. Empirical results are included to show that the robust model is superior to the standard model.

查看译文

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要