1 research outputs found
A Parallel Way to Select the Parameters of SVM Based on the Ant Optimization Algorithm
A large number of experimental data shows that Support Vector Machine (SVM)
algorithm has obvious advantages in text classification, handwriting
recognition, image classification, bioinformatics, and some other fields. To
some degree, the optimization of SVM depends on its kernel function and Slack
variable, the determinant of which is its parameters and c in the
classification function. That is to say,to optimize the SVM algorithm, the
optimization of the two parameters play a huge role. Ant Colony Optimization
(ACO) is optimization algorithm which simulate ants to find the optimal path.In
the available literature, we mix the ACO algorithm and Parallel algorithm
together to find a well parameters.Comment: 3 pages, 2 figures, 2 table