Model-Based Clustering Algorithm Implementation

MATLAB implementation for model-based clustering algorithms that processes complete MB clustering on given datasets. This implementation supports four fundamental model configurations with unequal unknown priors, employing Bayesian Information Criterion (BIC) for optimal model selection. The algorithm evaluates multiple Gaussian mixture models through Expectation-Maximization (EM) iterations and returns the BESTMODEL corresponding to the highest BIC score.