📄 gmmb_em_init_fcm1.m
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% GMMB_EM_INIT_FCM1
%
% initS = gmmb_em_init_fcm1(data, C, verbose)
%
% Create an initialization structure for EM,
% called from gmmb_em, see gmmb_em.
%
% Fuzzy C-means clustering means, uniform weight and covariance
% Requires the Fuzzy Logic Toolbox.
%
% Author(s):
% Pekka Paalanen <pekka.paalanen@lut.fi>
%
% Copyright:
%
% Bayesian Classifier with Gaussian Mixture Model Pdf
% functionality is Copyright (C) 2004 by Pekka Paalanen and
% Joni-Kristian Kamarainen.
%
% $Name: $ $Revision: 1.1 $ $Date: 2004/08/16 15:06:44 $
function initS = gmmb_em_init_fcm1(data, C, verbose);
D = size(data,2); % dimensions
% mu = zeros(D,C);
% mus initialization (thanks V. Kyrki)
if C>1
mu = fcm(data, C, [2.0 100 1e-3 verbose]).';
% fcm initialization has random nature, results will vary
else
mu = mean(data, 1).';
end
% covariances initialization
nsigma = covfixer2(diag(diag(cov(data))));
sigma = zeros(D,D,C);
for c = 1:C
sigma(:,:,c) = nsigma;
end
% weights initialization
weight = ones(C,1) * (1/C);
initS = struct(...
'mu', mu, ...
'sigma', sigma, ...
'weight', weight ...
);
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