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

1 files changed, 83 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/KPMstats/logistK_eval.m b/sourcecodes/bnt-master/KPMstats/logistK_eval.m
new file mode 100644
index 00000000..880a5f4b
--- /dev/null
+++ b/sourcecodes/bnt-master/KPMstats/logistK_eval.m
@@ -0,0 +1,83 @@
+function [post,lik,lli] = logistK_eval(beta,x,y)
+% [post,lik,lli] = logistK_eval(beta,x,y)
+%
+% Evaluate logistic regression model.
+% 
+% INPUT
+% 	beta 	dxk model coefficients (as returned by logistK)
+% 	x 	dxn matrix of n input column vectors
+% 	[y] 	kxn vector of class assignments
+%
+% OUTPUT
+% 	post 	kxn fitted class posteriors
+% 	lik 	1xn vector of sample likelihoods
+%	lli	log likelihood
+%
+% Let p(i,j) = exp(beta(:,j)'*x(:,i)),
+% Class j posterior for observation i is:
+%	post(j,i) = p(i,j) / (p(i,1) + ... p(i,k))
+% The likelihood of observation i given soft class assignments
+% y(:,i) is: 
+%	lik(i) = prod(post(:,i).^y(:,i))
+% The log-likelihood of the model given the labeled samples is:
+%	lli = sum(log(lik))
+% 
+% See also logistK.
+%
+% David Martin <dmartin@eecs.berkeley.edu> 
+% May 7, 2002
+
+% Copyright (C) 2002 David R. Martin <dmartin@eecs.berkeley.edu>
+%
+% This program is free software; you can redistribute it and/or
+% modify it under the terms of the GNU General Public License as
+% published by the Free Software Foundation; either version 2 of the
+% License, or (at your option) any later version.
+% 
+% This program is distributed in the hope that it will be useful, but
+% WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+% General Public License for more details.
+% 
+% You should have received a copy of the GNU General Public License
+% along with this program; if not, write to the Free Software
+% Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
+% 02111-1307, USA, or see http://www.gnu.org/copyleft/gpl.html.
+
+error(nargchk(2,3,nargin));
+
+% check sizes
+if size(beta,1) ~= size(x,1),
+  error('Inputs beta,x not the same height.');
+end
+if nargin > 3 & size(y,2) ~= size(x,2), 
+  error('Inputs x,y not the same length.'); 
+end
+
+% get sizes
+[d,k] = size(beta);
+[d,n] = size(x);
+
+% class posteriors
+post = zeros(k,n);
+bx = zeros(k,n);
+for j = 1:k, 
+  bx(j,:) = beta(:,j)'*x; 
+end
+for j = 1:k, 
+  post(j,:) = 1 ./ sum(exp(bx - repmat(bx(j,:),k,1)),1);
+end
+clear bx;
+
+% likelihood of each sample
+if nargout > 1,
+  y = y ./ repmat(sum(y,1),k,1); % L1-normalize class assignments
+  lik = prod(post.^y,1);
+end
+
+% total log likelihood
+if nargout > 2,
+  lli = sum(log(lik+eps));
+end;
+
+% eof