Mercurial > hg > camir-aes2014
annotate toolboxes/FullBNT-1.0.7/KPMstats/logist2Fit.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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children |
rev | line source |
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wolffd@0 | 1 function [beta, p] = logist2Fit(y, x, addOne, w) |
wolffd@0 | 2 % LOGIST2FIT 2 class logsitic classification |
wolffd@0 | 3 % function beta = logist2Fit(y,x, addOne) |
wolffd@0 | 4 % |
wolffd@0 | 5 % y(i) = 0/1 |
wolffd@0 | 6 % x(:,i) = i'th input - we optionally append 1s to last dimension |
wolffd@0 | 7 % w(i) = optional weight |
wolffd@0 | 8 % |
wolffd@0 | 9 % beta(j)- regression coefficient |
wolffd@0 | 10 |
wolffd@0 | 11 if nargin < 3, addOne = 1; end |
wolffd@0 | 12 if nargin < 4, w = 1; end |
wolffd@0 | 13 |
wolffd@0 | 14 Ncases = size(x,2); |
wolffd@0 | 15 if Ncases ~= length(y) |
wolffd@0 | 16 error(sprintf('size of data = %dx%d, size of labels=%d', size(x,1), size(x,2), length(y))) |
wolffd@0 | 17 end |
wolffd@0 | 18 if addOne |
wolffd@0 | 19 x = [x; ones(1,Ncases)]; |
wolffd@0 | 20 end |
wolffd@0 | 21 [beta, p] = logist2(y(:), x', w(:)); |
wolffd@0 | 22 beta = beta(:); |