From 8070dc963753142bb86c4ed698d91fd623ed28e7 Mon Sep 17 00:00:00 2001 From: ziejd2 Date: Thu, 28 Sep 2017 15:04:40 -0500 Subject: BNW using Octave instead of Matlab. This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02 --- sourcecodes/bnt-master/netlab3.3/netinit.m | 45 ++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 sourcecodes/bnt-master/netlab3.3/netinit.m (limited to 'sourcecodes/bnt-master/netlab3.3/netinit.m') diff --git a/sourcecodes/bnt-master/netlab3.3/netinit.m b/sourcecodes/bnt-master/netlab3.3/netinit.m new file mode 100644 index 00000000..f94e30b3 --- /dev/null +++ b/sourcecodes/bnt-master/netlab3.3/netinit.m @@ -0,0 +1,45 @@ +function net = netinit(net, prior) +%NETINIT Initialise the weights in a network. +% +% Description +% +% NET = NETINIT(NET, PRIOR) takes a network data structure 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 of the kind generated by +% MLPPRIOR, 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 +% MLPPRIOR, NETUNPAK, RBFPRIOR +% + +% Copyright (c) Ian T Nabney (1996-2001) + +if isstruct(prior) + if (isfield(net, 'mask')) + if find(sum(prior.index, 2)) ~= find(net.mask) + error('Index does not match mask'); + end + sig = sqrt(prior.index*prior.alpha); + % Weights corresponding to zeros in mask will not be used anyway + % Set their priors to one to avoid division by zero + sig = sig + (sig == 0); + sig = 1./sqrt(sig); + else + sig = 1./sqrt(prior.index*prior.alpha); + end + 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 + +if (isfield(net, 'mask')) + w = w(logical(net.mask)); +end +net = netunpak(net, w); + -- cgit 1.4.1