Article

Machine Learning

, Volume 61, Issue 1, pp 151-165

A Fast Dual Algorithm for Kernel Logistic Regression

  • S. S. KeerthiAffiliated withYahoo! Research Labs Email author 
  • , K. B. DuanAffiliated withControl Division, Department of Mechanical Engineering, National University of Singapore
  • , S. K. ShevadeAffiliated withDepartment of Computer Science and Automation, Indian Institute of Science
  • , A. N. PooAffiliated withControl Division, Department of Mechanical Engineering, National University of 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.

Keywords

classification logistic regression kernel methods SMO algorithm