Hierarchical Maximium Likelihood (HML) Clustering

バージョン 1.0.0.0 (3.23 KB) 作成者: Alok
This is a hierarchical clustering approach using maximum likelihood estimate.

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更新 2016/3/28

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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

引用

Alok (2022). Hierarchical Maximium Likelihood (HML) Clustering (https://www.mathworks.com/matlabcentral/fileexchange/56192-hierarchical-maximium-likelihood-hml-clustering), MATLAB Central File Exchange. 取得済み .

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作成: R2015b
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