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function net = rbfsetbf(net, options, x)
%RBFSETBF Set basis functions of RBF from data.
%
% Description
% NET = RBFSETBF(NET, OPTIONS, X) sets the basis functions of the RBF
% network NET so that they model the unconditional density of the
% dataset X. This is done by training a GMM with spherical covariances
% using GMMEM. The OPTIONS vector is passed to GMMEM. The widths of
% the functions are set by a call to RBFSETFW.
%
% See also
% RBFTRAIN, RBFSETFW, GMMEM
%
% Copyright (c) Ian T Nabney (1996-2001)
errstring = consist(net, 'rbf', x);
if ~isempty(errstring)
error(errstring);
end
% Create a spherical Gaussian mixture model
mix = gmm(net.nin, net.nhidden, 'spherical');
% Initialise the parameters from the input data
% Just use a small number of k means iterations
kmoptions = zeros(1, 18);
kmoptions(1) = -1; % Turn off warnings
kmoptions(14) = 5; % Just 5 iterations to get centres roughly right
mix = gmminit(mix, x, kmoptions);
% Train mixture model using EM algorithm
[mix, options] = gmmem(mix, x, options);
% Now set the centres of the RBF from the centres of the mixture model
net.c = mix.centres;
% options(7) gives scale of function widths
net = rbfsetfw(net, options(7));
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