stree_datasets/var_selec/best.txt

* Process all datasets set with stree_default: tanveer norm: False std: False discretize: False store in: stree_default
5 Fold Cross Validation with 10 random seeds [57, 31, 1714, 17, 23, 79, 83, 97, 7, 1]

Dataset                        Samp  Var Cls Nodes   Leaves  Depth   Accuracy        Time            Parameters                                   
============================== ===== === === ======= ======= ======= =============== =============== ============================================ 
balance-scale                    625   4   3   23.32   12.16    6.44 0.840160±0.0304 0.061757±0.0101 {"max_features": "sqrt", "splitter": "best"}
balloons                          16   4   2    5.04    3.02    2.86 0.703333±0.3279✔0.005872±0.0014 {"max_features": "sqrt", "splitter": "best"}
breast-cancer-wisc-diag          569  30   2    5.64    3.32    3.26 0.952206±0.0179 0.015298±0.0021 {"max_features": "sqrt", "splitter": "best"}
breast-cancer-wisc-prog          198  33   2    3.36    2.18    2.08 0.760692±0.0679 0.007594±0.0036 {"max_features": "sqrt", "splitter": "best"}
breast-cancer-wisc               699   9   2    8.40    4.70    4.16 0.956074±0.0150 0.018948±0.0032 {"max_features": "sqrt", "splitter": "best"}
breast-cancer                    286   9   2   12.64    6.82    4.96 0.722396±0.0477 0.021044±0.0058 {"max_features": "sqrt", "splitter": "best"}
cardiotocography-10clases       2126  21  10   78.96   39.98   10.00 0.777987±0.0284 0.453768±0.0424 {"max_features": "sqrt", "splitter": "best"}
cardiotocography-3clases        2126  21   3   35.60   18.30    7.18 0.888946±0.0132 0.206571±0.0161 {"max_features": "sqrt", "splitter": "best"}
conn-bench-sonar-mines-rocks     208  60   2   20.96   10.98    5.76 0.788467±0.0531✔0.030019±0.0050 {"max_features": "sqrt", "splitter": "best"}
cylinder-bands                   512  35   2   13.12    7.06    4.98 0.670706±0.0440 0.038204±0.0162 {"max_features": "sqrt", "splitter": "best"}
dermatology                      366  34   6   16.48    8.74    6.58 0.942488±0.0633 0.035710±0.0058 {"max_features": "sqrt", "splitter": "best"}
echocardiogram                   131  10   2    3.04    2.02    2.02 0.855157±0.0627★0.005411±0.0003 {"max_features": "sqrt", "splitter": "best"}
fertility                        100   9   2    1.00    1.00    1.00 0.880000±0.0548✔0.002806±0.0001 {"max_features": "sqrt", "splitter": "best"}
haberman-survival                306   3   2    4.88    2.94    2.42 0.726838±0.0467 0.011462±0.0070 {"max_features": "sqrt", "splitter": "best"}
heart-hungarian                  294  12   2    9.76    5.38    4.18 0.803063±0.0507 0.018199±0.0074 {"max_features": "sqrt", "splitter": "best"}
hepatitis                        155  19   2    7.16    4.08    3.78 0.796774±0.0707✔0.011034±0.0028 {"max_features": "sqrt", "splitter": "best"}
ilpd-indian-liver                583   9   2    1.00    1.00    1.00 0.713566±0.0380 0.009467±0.0005 {"max_features": "sqrt", "splitter": "best"}
ionosphere                       351  33   2    8.40    4.70    3.98 0.885171±0.0380✔0.019862±0.0052 {"max_features": "sqrt", "splitter": "best"}
iris                             150   4   3    5.00    3.00    3.00 0.955333±0.0295 0.009553±0.0005 {"max_features": "sqrt", "splitter": "best"}
led-display                     1000   7  10   42.04   21.52    7.56 0.698400±0.0279 0.223497±0.0188 {"max_features": "sqrt", "splitter": "best"}
libras                           360  90  15  110.64   55.82   13.18 0.628889±0.0689 0.282618±0.0300 {"max_features": "sqrt", "splitter": "best"}
low-res-spect                    531 100   9   21.96   11.48    6.26 0.675105±0.1328 0.082683±0.0332 {"max_features": "sqrt", "splitter": "best"}
lymphography                     148  18   4    8.92    4.96    4.12 0.695402±0.0960 0.016269±0.0079 {"max_features": "sqrt", "splitter": "best"}
mammographic                     961   5   2    7.80    4.40    3.86 0.800316±0.0287 0.040685±0.0097 {"max_features": "sqrt", "splitter": "best"}
molec-biol-promoter              106  57   2    9.88    5.44    3.82 0.795238±0.0885★0.011032±0.0022 {"max_features": "sqrt", "splitter": "best"}
musk-1                           476 166   2   17.20    9.10    6.36 0.803550±0.0400 0.054166±0.0146 {"max_features": "sqrt", "splitter": "best"}
oocytes_merluccius_nucleus_4d   1022  41   2    2.52    1.76    1.64 0.670453±0.0246 0.058849±0.0372 {"max_features": "sqrt", "splitter": "best"}
oocytes_merluccius_states_2f    1022  25   3   12.04    6.52    4.58 0.905669±0.0181 0.064227±0.0088 {"max_features": "sqrt", "splitter": "best"}
oocytes_trisopterus_nucleus_2f   912  25   2    9.16    5.08    3.76 0.632794±0.0745 0.063707±0.0250 {"max_features": "sqrt", "splitter": "best"}
oocytes_trisopterus_states_5b    912  32   3   11.88    6.44    4.68 0.832891±0.0341 0.079999±0.0122 {"max_features": "sqrt", "splitter": "best"}
parkinsons                       195  22   2    6.84    3.92    3.74 0.858974±0.0506 0.011659±0.0017 {"max_features": "sqrt", "splitter": "best"}
pima                             768   8   2    3.04    2.02    2.02 0.757917±0.0270 0.025315±0.0009 {"max_features": "sqrt", "splitter": "best"}
pittsburg-bridges-MATERIAL       106   7   3    4.76    2.88    2.84 0.851645±0.0780✔0.009979±0.0030 {"max_features": "sqrt", "splitter": "best"}
pittsburg-bridges-REL-L          103   7   3    9.24    5.12    4.18 0.675143±0.1020★0.017748±0.0051 {"max_features": "sqrt", "splitter": "best"}
pittsburg-bridges-SPAN            92   7   3   11.12    6.06    4.70 0.585731±0.1085 0.020438±0.0059 {"max_features": "sqrt", "splitter": "best"}
pittsburg-bridges-T-OR-D         102   7   2    1.04    1.02    1.02 0.861857±0.0763★0.002902±0.0006 {"max_features": "sqrt", "splitter": "best"}
planning                         182  12   2    1.00    1.00    1.00 0.714369±0.0715✔0.003860±0.0013 {"max_features": "sqrt", "splitter": "best"}
post-operative                    90   8   3    3.88    2.44    2.32 0.701111±0.0831✔0.006532±0.0030 {"max_features": "sqrt", "splitter": "best"}
seeds                            210   7   3    9.64    5.32    4.42 0.900952±0.0500 0.019858±0.0033 {"max_features": "sqrt", "splitter": "best"}
statlog-australian-credit        690  14   2    1.00    1.00    1.00 0.678261±0.0390✔0.013089±0.0006 {"max_features": "sqrt", "splitter": "best"}
statlog-german-credit           1000  24   2   13.16    7.08    5.44 0.738100±0.0301 0.059869±0.0056 {"max_features": "sqrt", "splitter": "best"}
statlog-heart                    270  13   2    8.72    4.86    4.20 0.784444±0.0474 0.017029±0.0050 {"max_features": "sqrt", "splitter": "best"}
statlog-image                   2310  18   7   31.24   16.12    8.58 0.902035±0.0306 0.283431±0.0240 {"max_features": "sqrt", "splitter": "best"}
statlog-vehicle                  846  18   4   44.20   22.60    8.56 0.653796±0.0398 0.144044±0.0179 {"max_features": "sqrt", "splitter": "best"}
synthetic-control                600  60   6   27.44   14.22    7.04 0.946667±0.0252✔0.059179±0.0063 {"max_features": "sqrt", "splitter": "best"}
tic-tac-toe                      958   9   2   17.08    9.04    6.16 0.771699±0.0365 0.060307±0.0094 {"max_features": "sqrt", "splitter": "best"}
vertebral-column-2clases         310   6   2    7.00    4.00    3.70 0.830645±0.0418 0.017122±0.0039 {"max_features": "sqrt", "splitter": "best"}
wine                             178  13   3   10.00    5.50    3.98 0.947778±0.0335 0.013517±0.0026 {"max_features": "sqrt", "splitter": "best"}
zoo                              101  16   7   18.92    9.96    7.40 0.927714±0.0655 0.030295±0.0027 {"max_features": "sqrt", "splitter": "best"}
✔ .....:  9
✔ .....:  1
★ .....:  4
** Accuracy compared to stree_default (liblinear-ovr) .:  0.9644
Time:  0h  2m 33s