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)))
