Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/netlab3.3/glminit.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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function net = glminit(net, prior) %GLMINIT Initialise the weights in a generalized linear model. % % Description % % NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and % sets the weights and biases by sampling from a Gaussian distribution. % If PRIOR is a scalar, then all of the parameters (weights and biases) % are sampled from a single isotropic Gaussian with inverse variance % equal to PRIOR. If PRIOR is a data structure similar to that in % MLPPRIOR but for a single layer of weights, then the parameters are % sampled from multiple Gaussians according to their groupings (defined % by the INDEX field) with corresponding variances (defined by the % ALPHA field). % % See also % GLM, GLMPAK, GLMUNPAK, MLPINIT, MLPPRIOR % % Copyright (c) Ian T Nabney (1996-2001) errstring = consist(net, 'glm'); if ~isempty(errstring); error(errstring); end if isstruct(prior) sig = 1./sqrt(prior.index*prior.alpha); w = sig'.*randn(1, net.nwts); elseif size(prior) == [1 1] w = randn(1, net.nwts).*sqrt(1/prior); else error('prior must be a scalar or a structure'); end net = glmunpak(net, w);