Hierarchical Maximium Likelihood (HML) Clustering
function [CLUSTER] = HML(X,CLASS,var)
% Cluster = HML(X,class,var)
%
% Hierarchical Maximum Likelihood algorithm
%
% 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.
%
% var: To hide plots put var = 0. Default value is 1.
%
% Ref. Sharma et al., Hierachical maximum likelihood clustering approach,
% IEEE Transaction on Biomedical Engineering, 2016
Cite As
Alok (2024). Hierarchical Maximium Likelihood (HML) Clustering (https://www.mathworks.com/matlabcentral/fileexchange/56192-hierarchical-maximium-likelihood-hml-clustering), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
HML/
Version | Published | Release Notes | |
---|---|---|---|
1.0.0.0 | . |