KLDA tuning with Social Evolutionary Learning Algorithm

Description

The Linear discriminant analysis (LDA) can be generalized into a nonlinear form – kernel LDA (KLDA) expediently by using the kernel functions.

In this MATLAB code, We used Social Evolutionary Learning Algorithm (SELA) for tuning the sigma in KLDA.

Data separation using the best sigma in the first iteration using SELA

Data separation using the best sigma in the last iteration using SELA

Convergence graph

We did not use any MATLAB toolbox for the implementation of this code, we just use MATLAB basic programming.