Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Optimisation of radial basis function classifiers using simulated annealing algorithm for cancer classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Wang, H.-Q. ; Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei, China ; Huang, D.-S. ; Wang, B.

A modified simulated annealing algorithm is developed and combined with the linear least square and gradient descent paradigms to optimise the structure of the radial basis function classifier (RBFC). The optimised RBFC is then applied to cancer classifications and compared with previous methods, such as least square support vector machine and Fisher discriminant analysis. Experimental results show that the optimised RBFC is not only parsimonious but also has better generalisation performance.

Published in:

Electronics Letters  (Volume:41 ,  Issue: 11 )