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A Fast Dual Algorithm for Kernel Logistic Regression |
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| Authors: | S. S. Keerthi K. B. Duan S. K. Shevade A. N. Poo |
| Affiliation: | (1) Yahoo! Research Labs, 210 S. DeLacey Avenue, Pasadena, CA 91105, USA;(2) Control Division, Department of Mechanical Engineering, National University of Singapore, Singapore;(3) Department of Computer Science and Automation, Indian Institute of Science, Bangalore, India;(4) Control Division, Department of Mechanical Engineering, National University of Singapore, Singapore |
| Abstract: | This paper gives a new iterative algorithm for kernel logistic regression. It is based on the solution of a dual problem using ideas similar to those of the Sequential Minimal Optimization algorithm for Support Vector Machines. Asymptotic convergence of the algorithm is proved. Computational experiments show that the algorithm is robust and fast. The algorithmic ideas can also be used to give a fast dual algorithm for solving the optimization problem arising in the inner loop of Gaussian Process classifiers. Editor: Shai Ben-David |
| Keywords: | classification logistic regression kernel methods SMO algorithm |
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