A Gaussian Mixture Model classifier written from scratch with Matlab for a school assignement.
The learning phase consists of a PCA on the learning data and the classic EM algorithm.
The MNIST database is used to test the classifier. It recognizes succesfully up to 97,87% of the test data using 8 components per class.