An improved algorithm for the solution of the regularization path of support vector machine

IEEE Transactions on Neural Networks
Chong-Jin OngJian-Bo Yang

Abstract

This paper describes an improved algorithm for the numerical solution to the support vector machine (SVM) classification problem for all values of the regularization parameter C . The algorithm is motivated by the work of Hastie and follows the main idea of tracking the optimality conditions of the SVM solution for ascending value of C . It differs from Hastie's approach in that the tracked path is not assumed to be 1-D. Instead, a multidimensional feasible space for the optimality condition is used to solve the tracking problem. Such a treatment allows the algorithm to properly handle data sets which Hastie's approach fails. These data sets are characterized by the presence of linearly dependent points (in the kernel space), duplicate points, or nearly duplicate points. Such data sets are quite common among many real-world data, especially those with nominal features. Other contributions of this paper include a unifying formulation of the tracking process in the form of a linear programming problem, update formula for the linear programs, considerations that guard against accumulation of errors resulting from the use of incremental updates, and routines to speed up the algorithm. The algorithm is implemented under the Matlab e...Continue Reading

References

Sep 24, 2004·IEEE Transactions on Neural Networks·Martin M S LeeDennis DeCoste
Apr 21, 2007·Neural Computation·Lacey Gunter, Ji Zhu
Oct 10, 2008·IEEE Transactions on Neural Networks·Gang WangFrederick H Lochovsky

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Citations

May 1, 2012·IEEE Transactions on Neural Networks and Learning Systems·Bin GuYue-Cheng Yu
May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Jisheng DaiWeichao Xu
Feb 24, 2011·IEEE Transactions on Neural Networks·Jian-Bo Yang, Chong-Jin Ong
Sep 9, 2011·IEEE Transactions on Neural Networks·Christopher SentelleMichael Georgiopoulos
Sep 2, 2011·IEEE Transactions on Neural Networks·Masayuki Karasuyama, Ichiro Takeuchi
Nov 5, 2010·IEEE Transactions on Neural Networks·Kris De BrabanterBart De Moor
May 27, 2015·IEEE Transactions on Neural Networks and Learning Systems·Christopher G SentelleMichael Georgiopoulos
May 2, 2015·Neural Networks : the Official Journal of the International Neural Network Society·Bin GuShuo Li
Apr 23, 2016·IEEE Transactions on Neural Networks and Learning Systems·Annabella Astorino, Antonio Fuduli
Apr 6, 2016·IEEE Transactions on Cybernetics· Lizhong Ding, Shizhong Liao
Mar 2, 2016·IEEE Transactions on Neural Networks and Learning Systems·Bin Gu, Victor S Sheng
Apr 14, 2016·IEEE Transactions on Neural Networks and Learning Systems·Xiaolin HuangJohan A K Suykens

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