Abstract
Fuzzy c-Means based Classifier (FCMC) is a simple approach to classification based on the clustering and parameter optimization methods. The computation time is improved by optimizing the matrix sizes in MATLAB code and by partly coded in Visual C with MEX function. For typical matrix computation and the numerical computation such as the eigenvalue decomposition of covariance matrices, MATLAB is faster than C/C++, though the repetitive computing with loop is usually slow by MATLAB. So, we try to optimize the computational time by mixing these two programming languages. When the number of training samples is more than a million, the total training time for FCMC is estimated to be more than three orders of magnitude smaller than LibSVM.
