prefix = au.get_groups_in_fname(trainfeatsf) expname = prefix + '.' + expname trainfeatsf = tstdir + os.path.sep + trainfeatsf testfeatsf = tstdir + os.path.sep + testfeatsf #test with grid search if scaled: texpname = expname + '.scaled.linearsvm' else: texpname = expname + '.linearsvm' #train grid search au.log.info('Grid search') bestc = au.get_best_c_param(aizko_svm, trainfeatsf, cgrid, outdir, texpname, 3, stratified, rocarea_opt, '') params[midx, didx, sidx, tidx] = bestc au.log.info('Testing ' + testfeatsf + ' with C = ' + str(bestc)) res = au.svm_linear_test(aizko_svm, trainfeatsf, testfeatsf, texpname, outdir, bestc, redoing, rocarea_opt) results[midx, didx, sidx, tidx, :] = res rc += 1 au.log.info('Results: ' + ' '.join(map(str, res)))