@inproceedings{31cb8613ae2847ab92b3bef915427f55,
title = "Robust 1-norm soft margin smooth support vector machine",
abstract = "Based on studies and experiments on the loss term of SVMs, we argue that 1-norm measurement is better than 2-norm measurement for outlier resistance. Thus, we modify the previous 2-norm soft margin smooth support vector machine (SSVM 2) to propose a new 1-norm soft margin smooth support vector machine (SSVM 1). Both SSVMs can be solved in primal form without a sophisticated optimization solver. We also propose a heuristic method for outlier filtering which costs little in training process and improves the ability of outlier resistance a lot. The experimental results show that SSVM 1 with outlier filtering heuristic performs well not only on the clean, but also the polluted synthetic and benchmark UCI datasets.",
keywords = "Classification, Outlier resistance, Robustness, Smooth technique, Support vector machine",
author = "Chien, {Li Jen} and Yuh-Jye Lee and Kao, {Zhi Peng} and Chang, {Chih Cheng}",
year = "2010",
month = nov,
day = "8",
doi = "10.1007/978-3-642-15381-5_18",
language = "English",
isbn = "3642153801",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "145--152",
booktitle = "Intelligent Data Engineering and Automated Learning, IDEAL 2010 - 11th International Conference, Proceedings",
note = "11th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2010 ; Conference date: 01-09-2010 Through 03-09-2010",
}