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-rw-r--r--sourcecodes/bnt-master/KPMstats/logist2Fit.m22
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diff --git a/sourcecodes/bnt-master/KPMstats/logist2Fit.m b/sourcecodes/bnt-master/KPMstats/logist2Fit.m
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+function [beta, p] = logist2Fit(y, x, addOne, w)
+% LOGIST2FIT 2 class logsitic classification
+% function beta = logist2Fit(y,x, addOne)
+%
+% y(i) = 0/1
+% x(:,i) = i'th input - we optionally append 1s to last dimension
+% w(i) = optional weight
+%
+% beta(j)- regression coefficient
+
+if nargin < 3, addOne = 1; end
+if nargin < 4, w = 1; end
+
+Ncases = size(x,2);
+if Ncases ~= length(y)
+  error(sprintf('size of data = %dx%d, size of labels=%d', size(x,1), size(x,2), length(y)))
+end
+if addOne
+  x = [x; ones(1,Ncases)];
+end
+[beta, p] = logist2(y(:), x', w(:));
+beta = beta(:);