Mercurial > hg > camir-aes2014
diff core/tools/machine_learning/save_svmlight_inequalities.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
---|---|
date | Tue, 10 Feb 2015 15:05:51 +0000 |
parents | |
children |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/core/tools/machine_learning/save_svmlight_inequalities.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,57 @@ +function success = save_svmlight_inequalities(lhs, rhs, factors, file) +% success = save_svmlight_inequalities(lhs, rhs, file) +% +% saves the optimisation problem given by lhs and rhs to +% a svmlight data file. the individual equations can +% be weighted using +% +% success = save_svmlight_inequalities(lhs, rhs, factors, file) + +if nargin == 3 + file = factors; + factors = []; +end + +% open file +fid = fopen(file, 'w+'); +if fid < 1 + success = 0; + return; +end + +try + % write individual constraint rows + for i = 1:size(lhs,1) + + % --- + % print rows:" rhs #fnum:#fval #fnum:#fval #fnum:#fval ..." + % --- + + % print right hand side + fprintf(fid,'%d ', rhs(i)); + + % print cost factors if availablefactor + if (numel(lhs{i,1}) > 0) && (numel(factors) >= i) + + fprintf(fid,'cost:%f ', factors(i)); + end + + % print left hand side + for j = 1:numel(lhs{i,1}) + + fprintf(fid,'%d:%2.16f ', lhs{i,1}(j), lhs{i,2}(j)); + end + + % finish line + fprintf(fid,'\n'); + end +catch + success = 0; + fclose(fid); + return; +end +success = 1; +fclose(fid); + + + \ No newline at end of file