Hierarchical Maximium Likelihood (HML) Clustering

function [CLUSTER] = HML(X,CLASS,var)
% Cluster = HML(X,class,var)
%
% Hierarchical Maximum Likelihood algorithm
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% Input
% X: data of size N x d (where N = num of samples; and, d = dimension).
% class: (optional) if not specified then all classes from 1 to n will be
% produced. If class = k then samples will be classified into k
% clusters only. A range of values of class can also be provided.
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% var: To hide plots put var = 0. Default value is 1.
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% Ref. Sharma et al., Hierachical maximum likelihood clustering approach,
% IEEE Transaction on Biomedical Engineering, 2016