Abstract: SVM ( Support Vector Machine) is a linear classifier with the largest interval defined in the feature
space． Values of these parameters determine the learning performance and generalization ability． In order to
solve the problem of SVM parameter selection，the modified vortex search algorithm is used to find the optimal
fitness function． The simulation results show that the modified vortex search algorithm is an effective SVM
parameter selection method． It is beneficial to jump out of the local minimum，and its performance is not lower
than the vortex search algorithm．

Key words: support vector machine ( SVM) , modified vortex search, parameter optimization, meta heuristic
optimization algorithm, the local minimum