Current directory is /mnt/home.dokt/xfrancv/workAdding path for the Statistical Pattern Recognition Toolbox...Creating training set:Input file: daniel_martinec1.mat, label: 1Input file: daniel_martinec10.mat, label: 10Input file: daniel_martinec2.mat, label: 2Input file: daniel_martinec3.mat, label: 3Input file: daniel_martinec4.mat, label: 4Input file: daniel_martinec5.mat, label: 5Input file: daniel_martinec6.mat, label: 6Input file: daniel_martinec7.mat, label: 7Input file: daniel_martinec8.mat, label: 8Input file: daniel_martinec9.mat, label: 9Input file: honza_cech1.mat, label: 1Input file: honza_cech10.mat, label: 10Input file: honza_cech2.mat, label: 2Input file: honza_cech3.mat, label: 3Input file: honza_cech4.mat, label: 4Input file: honza_cech5.mat, label: 5Input file: honza_cech6.mat, label: 6Input file: honza_cech7.mat, label: 7Input file: honza_cech8.mat, label: 8Input file: honza_cech9.mat, label: 9Input file: jana_kostkova1.mat, label: 1Input file: jana_kostkova10.mat, label: 10Input file: jana_kostkova2.mat, label: 2Input file: jana_kostkova3.mat, label: 3Input file: jana_kostkova4.mat, label: 4Input file: jana_kostkova5.mat, label: 5Input file: jana_kostkova6.mat, label: 6Input file: jana_kostkova7.mat, label: 7Input file: jana_kostkova8.mat, label: 8Input file: jana_kostkova9.mat, label: 9Input file: martin_matousek1.mat, label: 1Input file: martin_matousek10.mat, label: 10Input file: martin_matousek2.mat, label: 2Input file: martin_matousek3.mat, label: 3Input file: martin_matousek4.mat, label: 4Input file: martin_matousek5.mat, label: 5Input file: martin_matousek6.mat, label: 6Input file: martin_matousek7.mat, label: 7Input file: martin_matousek8.mat, label: 8Input file: martin_matousek9.mat, label: 9Input file: martin_barva1.mat, label: 1Input file: martin_barva10.mat, label: 10Input file: martin_barva2.mat, label: 2Input file: martin_barva3.mat, label: 3Input file: martin_barva4.mat, label: 4Input file: martin_barva6.mat, label: 6Input file: martin_barva7.mat, label: 7Input file: martin_barva8.mat, label: 8Input file: martin_barva9.mat, label: 9Input file: vojta_franc1.mat, label: 1Input file: vojta_franc10.mat, label: 10Input file: vojta_franc2.mat, label: 2Input file: vojta_franc3.mat, label: 3Input file: vojta_franc4.mat, label: 4Input file: vojta_franc5.mat, label: 5Input file: vojta_franc6.mat, label: 6Input file: vojta_franc7.mat, label: 7Input file: vojta_franc8.mat, label: 8Input file: vojta_franc9.mat, label: 9Saving data to: ../../data/ocr_numerals/OcrTrndata.mat>> >> >> >> >> >> Tuning multi-class SVM classifier.>> Model 1/5: ker=rbf, C=Inf, arg=1.000000 fold 1/5: training, testing, tst_err = 0.8559fold 2/5: training, testing, tst_err = 0.8831fold 3/5: training, testing, tst_err = 0.8932fold 4/5: training, testing, tst_err = 0.8966fold 5/5: training, testing, tst_err = 0.8831cross-validation error = 0.8824 (best so far)Model 2/5: ker=rbf, C=Inf, arg=2.500000 fold 1/5: training, testing, tst_err = 0.0746fold 2/5: training, testing, tst_err = 0.0864fold 3/5: training, testing, tst_err = 0.0780fold 4/5: training, testing, tst_err = 0.0441fold 5/5: training, testing, tst_err = 0.0627cross-validation error = 0.0692 (best so far)Model 3/5: ker=rbf, C=Inf, arg=5.000000 fold 1/5: training, testing, tst_err = 0.0475fold 2/5: training, testing, tst_err = 0.0390fold 3/5: training, testing, tst_err = 0.0458fold 4/5: training, testing, tst_err = 0.0237fold 5/5: training, testing, tst_err = 0.0288cross-validation error = 0.0369 (best so far)Model 4/5: ker=rbf, C=Inf, arg=7.500000 fold 1/5: training, testing, tst_err = 0.0424fold 2/5: training, testing, tst_err = 0.0407fold 3/5: training, testing, tst_err = 0.0441fold 4/5: training, testing, tst_err = 0.0288fold 5/5: training, testing, tst_err = 0.0322cross-validation error = 0.0376Model 5/5: ker=rbf, C=Inf, arg=10.000000 fold 1/5: training, testing, tst_err = 0.0441fold 2/5: training, testing, tst_err = 0.0424fold 3/5: training, testing, tst_err = 0.0458fold 4/5: training, testing, tst_err = 0.0288fold 5/5: training, testing, tst_err = 0.0356cross-validation error = 0.0393best model: ker=rbf, C=Inf, arg=5.000000 cross-validation error = 0.0369>> >> Saving results to: ocrtuning>> >> >> >> >> >> >> >>