ServerRun 7469
Creatorfavre
Programboostexter
Datasetletter-recognition
Task typeMulticlassClassification
Created7y12d ago
DownloadLogin required!
Done! Flag_green
2m32s
52M
MulticlassClassification
0.107
0.143

Log file

... (lines omitted) ...
rnd  633: wh-err= 0.999779  th-err= 0.055796  test=       nan  train= 0.1128571 
rnd  634: wh-err= 0.999789  th-err= 0.055785  test=       nan  train= 0.1128571 
rnd  635: wh-err= 0.999784  th-err= 0.055773  test=       nan  train= 0.1127857 
rnd  636: wh-err= 0.999787  th-err= 0.055761  test=       nan  train= 0.1127143 
rnd  637: wh-err= 0.999776  th-err= 0.055748  test=       nan  train= 0.1130000 
rnd  638: wh-err= 0.999784  th-err= 0.055736  test=       nan  train= 0.1130000 
rnd  639: wh-err= 0.999783  th-err= 0.055724  test=       nan  train= 0.1127143 
rnd  640: wh-err= 0.999759  th-err= 0.055711  test=       nan  train= 0.1127857 
rnd  641: wh-err= 0.999774  th-err= 0.055698  test=       nan  train= 0.1125000 
rnd  642: wh-err= 0.999793  th-err= 0.055686  test=       nan  train= 0.1127143 
rnd  643: wh-err= 0.999796  th-err= 0.055675  test=       nan  train= 0.1125000 
rnd  644: wh-err= 0.999796  th-err= 0.055664  test=       nan  train= 0.1127143 
rnd  645: wh-err= 0.999814  th-err= 0.055653  test=       nan  train= 0.1128571 
rnd  646: wh-err= 0.999797  th-err= 0.055642  test=       nan  train= 0.1125714 
rnd  647: wh-err= 0.999783  th-err= 0.055630  test=       nan  train= 0.1125000 
rnd  648: wh-err= 0.999790  th-err= 0.055618  test=       nan  train= 0.1126429 
rnd  649: wh-err= 0.999798  th-err= 0.055607  test=       nan  train= 0.1127857 
rnd  650: wh-err= 0.999790  th-err= 0.055595  test=       nan  train= 0.1120000 
rnd  651: wh-err= 0.999793  th-err= 0.055584  test=       nan  train= 0.1117857 
rnd  652: wh-err= 0.999769  th-err= 0.055571  test=       nan  train= 0.1119286 
rnd  653: wh-err= 0.999752  th-err= 0.055557  test=       nan  train= 0.1115000 
rnd  654: wh-err= 0.999780  th-err= 0.055545  test=       nan  train= 0.1120714 
rnd  655: wh-err= 0.999784  th-err= 0.055533  test=       nan  train= 0.1116429 
rnd  656: wh-err= 0.999793  th-err= 0.055521  test=       nan  train= 0.1117143 
rnd  657: wh-err= 0.999786  th-err= 0.055510  test=       nan  train= 0.1118571 
rnd  658: wh-err= 0.999799  th-err= 0.055498  test=       nan  train= 0.1117857 
rnd  659: wh-err= 0.999790  th-err= 0.055487  test=       nan  train= 0.1117857 
rnd  660: wh-err= 0.999784  th-err= 0.055475  test=       nan  train= 0.1115714 
rnd  661: wh-err= 0.999799  th-err= 0.055464  test=       nan  train= 0.1117143 
rnd  662: wh-err= 0.999824  th-err= 0.055454  test=       nan  train= 0.1117857 
rnd  663: wh-err= 0.999794  th-err= 0.055442  test=       nan  train= 0.1120000 
rnd  664: wh-err= 0.999801  th-err= 0.055431  test=       nan  train= 0.1119286 
rnd  665: wh-err= 0.999739  th-err= 0.055417  test=       nan  train= 0.1118571 
rnd  666: wh-err= 0.999773  th-err= 0.055404  test=       nan  train= 0.1120000 
rnd  667: wh-err= 0.999770  th-err= 0.055392  test=       nan  train= 0.1121429 
rnd  668: wh-err= 0.999794  th-err= 0.055380  test=       nan  train= 0.1121429 
rnd  669: wh-err= 0.999788  th-err= 0.055368  test=       nan  train= 0.1122857 
rnd  670: wh-err= 0.999788  th-err= 0.055357  test=       nan  train= 0.1119286 
rnd  671: wh-err= 0.999793  th-err= 0.055345  test=       nan  train= 0.1125714 
rnd  672: wh-err= 0.999789  th-err= 0.055334  test=       nan  train= 0.1120714 
rnd  673: wh-err= 0.999743  th-err= 0.055319  test=       nan  train= 0.1114286 
rnd  674: wh-err= 0.999788  th-err= 0.055308  test=       nan  train= 0.1115000 
rnd  675: wh-err= 0.999794  th-err= 0.055296  test=       nan  train= 0.1112143 
rnd  676: wh-err= 0.999780  th-err= 0.055284  test=       nan  train= 0.1112143 
rnd  677: wh-err= 0.999742  th-err= 0.055270  test=       nan  train= 0.1113571 
rnd  678: wh-err= 0.999801  th-err= 0.055259  test=       nan  train= 0.1114286 
rnd  679: wh-err= 0.999761  th-err= 0.055245  test=       nan  train= 0.1115000 
rnd  680: wh-err= 0.999794  th-err= 0.055234  test=       nan  train= 0.1115000 
rnd  681: wh-err= 0.999792  th-err= 0.055223  test=       nan  train= 0.1115714 
rnd  682: wh-err= 0.999783  th-err= 0.055211  test=       nan  train= 0.1115000 
rnd  683: wh-err= 0.999818  th-err= 0.055201  test=       nan  train= 0.1116429 
rnd  684: wh-err= 0.999836  th-err= 0.055192  test=       nan  train= 0.1116429 
rnd  685: wh-err= 0.999820  th-err= 0.055182  test=       nan  train= 0.1115714 
rnd  686: wh-err= 0.999808  th-err= 0.055171  test=       nan  train= 0.1115000 
rnd  687: wh-err= 0.999802  th-err= 0.055160  test=       nan  train= 0.1114286 
rnd  688: wh-err= 0.999823  th-err= 0.055150  test=       nan  train= 0.1116429 
rnd  689: wh-err= 0.999794  th-err= 0.055139  test=       nan  train= 0.1115714 
rnd  690: wh-err= 0.999806  th-err= 0.055128  test=       nan  train= 0.1116429 
rnd  691: wh-err= 0.999805  th-err= 0.055118  test=       nan  train= 0.1115000 
rnd  692: wh-err= 0.999807  th-err= 0.055107  test=       nan  train= 0.1109286 
rnd  693: wh-err= 0.999804  th-err= 0.055096  test=       nan  train= 0.1112143 
rnd  694: wh-err= 0.999807  th-err= 0.055085  test=       nan  train= 0.1114286 
rnd  695: wh-err= 0.999779  th-err= 0.055073  test=       nan  train= 0.1112143 
rnd  696: wh-err= 0.999812  th-err= 0.055063  test=       nan  train= 0.1115714 
rnd  697: wh-err= 0.999811  th-err= 0.055053  test=       nan  train= 0.1115714 
rnd  698: wh-err= 0.999809  th-err= 0.055042  test=       nan  train= 0.1114286 
rnd  699: wh-err= 0.999812  th-err= 0.055032  test=       nan  train= 0.1111429 
rnd  700: wh-err= 0.999798  th-err= 0.055021  test=       nan  train= 0.1113571 
rnd  701: wh-err= 0.999817  th-err= 0.055011  test=       nan  train= 0.1116429 
rnd  702: wh-err= 0.999808  th-err= 0.055000  test=       nan  train= 0.1120714 
rnd  703: wh-err= 0.999823  th-err= 0.054990  test=       nan  train= 0.1115714 
rnd  704: wh-err= 0.999834  th-err= 0.054981  test=       nan  train= 0.1115714 
rnd  705: wh-err= 0.999820  th-err= 0.054971  test=       nan  train= 0.1117143 
rnd  706: wh-err= 0.999809  th-err= 0.054961  test=       nan  train= 0.1105714 
rnd  707: wh-err= 0.999792  th-err= 0.054949  test=       nan  train= 0.1105000 
rnd  708: wh-err= 0.999804  th-err= 0.054939  test=       nan  train= 0.1104286 
rnd  709: wh-err= 0.999821  th-err= 0.054929  test=       nan  train= 0.1105714 
rnd  710: wh-err= 0.999827  th-err= 0.054919  test=       nan  train= 0.1106429 
rnd  711: wh-err= 0.999824  th-err= 0.054909  test=       nan  train= 0.1101429 
rnd  712: wh-err= 0.999821  th-err= 0.054900  test=       nan  train= 0.1103571 
rnd  713: wh-err= 0.999834  th-err= 0.054891  test=       nan  train= 0.1105714 
rnd  714: wh-err= 0.999818  th-err= 0.054881  test=       nan  train= 0.1105000 
rnd  715: wh-err= 0.999818  th-err= 0.054871  test=       nan  train= 0.1112857 
rnd  716: wh-err= 0.999797  th-err= 0.054859  test=       nan  train= 0.1112857 
rnd  717: wh-err= 0.999852  th-err= 0.054851  test=       nan  train= 0.1113571 
rnd  718: wh-err= 0.999846  th-err= 0.054843  test=       nan  train= 0.1112143 
rnd  719: wh-err= 0.999819  th-err= 0.054833  test=       nan  train= 0.1111429 
rnd  720: wh-err= 0.999829  th-err= 0.054824  test=       nan  train= 0.1112857 
rnd  721: wh-err= 0.999824  th-err= 0.054814  test=       nan  train= 0.1113571 
rnd  722: wh-err= 0.999856  th-err= 0.054806  test=       nan  train= 0.1113571 
rnd  723: wh-err= 0.999837  th-err= 0.054797  test=       nan  train= 0.1112857 
rnd  724: wh-err= 0.999839  th-err= 0.054788  test=       nan  train= 0.1112143 
rnd  725: wh-err= 0.999852  th-err= 0.054780  test=       nan  train= 0.1115000 
rnd  726: wh-err= 0.999838  th-err= 0.054771  test=       nan  train= 0.1115000 
rnd  727: wh-err= 0.999785  th-err= 0.054760  test=       nan  train= 0.1112143 
rnd  728: wh-err= 0.999836  th-err= 0.054751  test=       nan  train= 0.1113571 
rnd  729: wh-err= 0.999828  th-err= 0.054741  test=       nan  train= 0.1111429 
rnd  730: wh-err= 0.999826  th-err= 0.054732  test=       nan  train= 0.1111429 
rnd  731: wh-err= 0.999851  th-err= 0.054723  test=       nan  train= 0.1110714 
rnd  732: wh-err= 0.999830  th-err= 0.054714  test=       nan  train= 0.1110714 
rnd  733: wh-err= 0.999840  th-err= 0.054705  test=       nan  train= 0.1108571 
rnd  734: wh-err= 0.999842  th-err= 0.054697  test=       nan  train= 0.1106429 
rnd  735: wh-err= 0.999810  th-err= 0.054686  test=       nan  train= 0.1107857 
rnd  736: wh-err= 0.999823  th-err= 0.054677  test=       nan  train= 0.1102857 
rnd  737: wh-err= 0.999825  th-err= 0.054667  test=       nan  train= 0.1101429 
rnd  738: wh-err= 0.999808  th-err= 0.054657  test=       nan  train= 0.1096429 
rnd  739: wh-err= 0.999814  th-err= 0.054646  test=       nan  train= 0.1099286 
rnd  740: wh-err= 0.999795  th-err= 0.054635  test=       nan  train= 0.1102143 
rnd  741: wh-err= 0.999834  th-err= 0.054626  test=       nan  train= 0.1107143 
rnd  742: wh-err= 0.999835  th-err= 0.054617  test=       nan  train= 0.1107143 
rnd  743: wh-err= 0.999828  th-err= 0.054608  test=       nan  train= 0.1105000 
rnd  744: wh-err= 0.999832  th-err= 0.054599  test=       nan  train= 0.1102857 
rnd  745: wh-err= 0.999847  th-err= 0.054590  test=       nan  train= 0.1100714 
rnd  746: wh-err= 0.999844  th-err= 0.054582  test=       nan  train= 0.1102857 
rnd  747: wh-err= 0.999849  th-err= 0.054573  test=       nan  train= 0.1101429 
rnd  748: wh-err= 0.999844  th-err= 0.054565  test=       nan  train= 0.1102143 
rnd  749: wh-err= 0.999825  th-err= 0.054555  test=       nan  train= 0.1100714 
rnd  750: wh-err= 0.999814  th-err= 0.054545  test=       nan  train= 0.1100714 
rnd  751: wh-err= 0.999831  th-err= 0.054536  test=       nan  train= 0.1100714 
rnd  752: wh-err= 0.999839  th-err= 0.054527  test=       nan  train= 0.1099286 
rnd  753: wh-err= 0.999832  th-err= 0.054518  test=       nan  train= 0.1102143 
rnd  754: wh-err= 0.999827  th-err= 0.054509  test=       nan  train= 0.1102143 
rnd  755: wh-err= 0.999844  th-err= 0.054500  test=       nan  train= 0.1106429 
rnd  756: wh-err= 0.999835  th-err= 0.054491  test=       nan  train= 0.1102857 
rnd  757: wh-err= 0.999832  th-err= 0.054482  test=       nan  train= 0.1106429 
rnd  758: wh-err= 0.999834  th-err= 0.054473  test=       nan  train= 0.1108571 
rnd  759: wh-err= 0.999822  th-err= 0.054463  test=       nan  train= 0.1109286 
rnd  760: wh-err= 0.999824  th-err= 0.054454  test=       nan  train= 0.1100714 
rnd  761: wh-err= 0.999836  th-err= 0.054445  test=       nan  train= 0.1100714 
rnd  762: wh-err= 0.999821  th-err= 0.054435  test=       nan  train= 0.1099286 
rnd  763: wh-err= 0.999823  th-err= 0.054425  test=       nan  train= 0.1100714 
rnd  764: wh-err= 0.999836  th-err= 0.054416  test=       nan  train= 0.1101429 
rnd  765: wh-err= 0.999831  th-err= 0.054407  test=       nan  train= 0.1098571 
rnd  766: wh-err= 0.999814  th-err= 0.054397  test=       nan  train= 0.1099286 
rnd  767: wh-err= 0.999829  th-err= 0.054388  test=       nan  train= 0.1099286 
rnd  768: wh-err= 0.999801  th-err= 0.054377  test=       nan  train= 0.1099286 
rnd  769: wh-err= 0.999854  th-err= 0.054369  test=       nan  train= 0.1099286 
rnd  770: wh-err= 0.999848  th-err= 0.054361  test=       nan  train= 0.1100000 
rnd  771: wh-err= 0.999832  th-err= 0.054352  test=       nan  train= 0.1100714 
rnd  772: wh-err= 0.999860  th-err= 0.054344  test=       nan  train= 0.1098571 
rnd  773: wh-err= 0.999839  th-err= 0.054335  test=       nan  train= 0.1102143 
rnd  774: wh-err= 0.999850  th-err= 0.054327  test=       nan  train= 0.1100000 
rnd  775: wh-err= 0.999852  th-err= 0.054319  test=       nan  train= 0.1098571 
rnd  776: wh-err= 0.999848  th-err= 0.054311  test=       nan  train= 0.1096429 
rnd  777: wh-err= 0.999851  th-err= 0.054303  test=       nan  train= 0.1097857 
rnd  778: wh-err= 0.999854  th-err= 0.054295  test=       nan  train= 0.1099286 
rnd  779: wh-err= 0.999842  th-err= 0.054286  test=       nan  train= 0.1094286 
rnd  780: wh-err= 0.999876  th-err= 0.054280  test=       nan  train= 0.1094286 
rnd  781: wh-err= 0.999855  th-err= 0.054272  test=       nan  train= 0.1095714 
rnd  782: wh-err= 0.999865  th-err= 0.054264  test=       nan  train= 0.1097143 
rnd  783: wh-err= 0.999843  th-err= 0.054256  test=       nan  train= 0.1096429 
rnd  784: wh-err= 0.999829  th-err= 0.054247  test=       nan  train= 0.1094286 
rnd  785: wh-err= 0.999837  th-err= 0.054238  test=       nan  train= 0.1095000 
rnd  786: wh-err= 0.999863  th-err= 0.054230  test=       nan  train= 0.1097143 
rnd  787: wh-err= 0.999829  th-err= 0.054221  test=       nan  train= 0.1097857 
rnd  788: wh-err= 0.999843  th-err= 0.054212  test=       nan  train= 0.1097857 
rnd  789: wh-err= 0.999848  th-err= 0.054204  test=       nan  train= 0.1094286 
rnd  790: wh-err= 0.999856  th-err= 0.054196  test=       nan  train= 0.1095000 
rnd  791: wh-err= 0.999868  th-err= 0.054189  test=       nan  train= 0.1094286 
rnd  792: wh-err= 0.999848  th-err= 0.054181  test=       nan  train= 0.1094286 
rnd  793: wh-err= 0.999877  th-err= 0.054174  test=       nan  train= 0.1094286 
rnd  794: wh-err= 0.999852  th-err= 0.054166  test=       nan  train= 0.1092857 
rnd  795: wh-err= 0.999855  th-err= 0.054158  test=       nan  train= 0.1090000 
rnd  796: wh-err= 0.999865  th-err= 0.054151  test=       nan  train= 0.1088571 
rnd  797: wh-err= 0.999862  th-err= 0.054144  test=       nan  train= 0.1091429 
rnd  798: wh-err= 0.999836  th-err= 0.054135  test=       nan  train= 0.1093571 
rnd  799: wh-err= 0.999839  th-err= 0.054126  test=       nan  train= 0.1093571 
rnd  800: wh-err= 0.999850  th-err= 0.054118  test=       nan  train= 0.1090714 
rnd  801: wh-err= 0.999812  th-err= 0.054108  test=       nan  train= 0.1090000 
rnd  802: wh-err= 0.999869  th-err= 0.054101  test=       nan  train= 0.1091429 
rnd  803: wh-err= 0.999893  th-err= 0.054095  test=       nan  train= 0.1090714 
rnd  804: wh-err= 0.999878  th-err= 0.054088  test=       nan  train= 0.1090000 
rnd  805: wh-err= 0.999864  th-err= 0.054081  test=       nan  train= 0.1090714 
rnd  806: wh-err= 0.999853  th-err= 0.054073  test=       nan  train= 0.1090714 
rnd  807: wh-err= 0.999854  th-err= 0.054065  test=       nan  train= 0.1088571 
rnd  808: wh-err= 0.999858  th-err= 0.054057  test=       nan  train= 0.1091429 
rnd  809: wh-err= 0.999857  th-err= 0.054050  test=       nan  train= 0.1092143 
rnd  810: wh-err= 0.999853  th-err= 0.054042  test=       nan  train= 0.1090714 
rnd  811: wh-err= 0.999896  th-err= 0.054036  test=       nan  train= 0.1091429 
rnd  812: wh-err= 0.999880  th-err= 0.054030  test=       nan  train= 0.1090714 
rnd  813: wh-err= 0.999869  th-err= 0.054023  test=       nan  train= 0.1090714 
rnd  814: wh-err= 0.999843  th-err= 0.054014  test=       nan  train= 0.1095714 
rnd  815: wh-err= 0.999878  th-err= 0.054007  test=       nan  train= 0.1095714 
rnd  816: wh-err= 0.999857  th-err= 0.054000  test=       nan  train= 0.1096429 
rnd  817: wh-err= 0.999873  th-err= 0.053993  test=       nan  train= 0.1097143 
rnd  818: wh-err= 0.999842  th-err= 0.053984  test=       nan  train= 0.1096429 
rnd  819: wh-err= 0.999844  th-err= 0.053976  test=       nan  train= 0.1091429 
rnd  820: wh-err= 0.999852  th-err= 0.053968  test=       nan  train= 0.1092143 
rnd  821: wh-err= 0.999859  th-err= 0.053960  test=       nan  train= 0.1090714 
rnd  822: wh-err= 0.999864  th-err= 0.053953  test=       nan  train= 0.1090000 
rnd  823: wh-err= 0.999875  th-err= 0.053946  test=       nan  train= 0.1089286 
rnd  824: wh-err= 0.999866  th-err= 0.053939  test=       nan  train= 0.1089286 
rnd  825: wh-err= 0.999873  th-err= 0.053932  test=       nan  train= 0.1091429 
rnd  826: wh-err= 0.999870  th-err= 0.053925  test=       nan  train= 0.1092857 
rnd  827: wh-err= 0.999872  th-err= 0.053918  test=       nan  train= 0.1091429 
rnd  828: wh-err= 0.999867  th-err= 0.053911  test=       nan  train= 0.1084286 
rnd  829: wh-err= 0.999870  th-err= 0.053904  test=       nan  train= 0.1087857 
rnd  830: wh-err= 0.999874  th-err= 0.053897  test=       nan  train= 0.1085714 
rnd  831: wh-err= 0.999857  th-err= 0.053889  test=       nan  train= 0.1085714 
rnd  832: wh-err= 0.999877  th-err= 0.053883  test=       nan  train= 0.1088571 
rnd  833: wh-err= 0.999856  th-err= 0.053875  test=       nan  train= 0.1090000 
rnd  834: wh-err= 0.999866  th-err= 0.053868  test=       nan  train= 0.1090714 
rnd  835: wh-err= 0.999859  th-err= 0.053860  test=       nan  train= 0.1090000 
rnd  836: wh-err= 0.999874  th-err= 0.053854  test=       nan  train= 0.1087857 
rnd  837: wh-err= 0.999880  th-err= 0.053847  test=       nan  train= 0.1089286 
rnd  838: wh-err= 0.999884  th-err= 0.053841  test=       nan  train= 0.1089286 
rnd  839: wh-err= 0.999876  th-err= 0.053834  test=       nan  train= 0.1089286 
rnd  840: wh-err= 0.999891  th-err= 0.053828  test=       nan  train= 0.1090000 
rnd  841: wh-err= 0.999872  th-err= 0.053821  test=       nan  train= 0.1091429 
rnd  842: wh-err= 0.999881  th-err= 0.053815  test=       nan  train= 0.1090000 
rnd  843: wh-err= 0.999857  th-err= 0.053807  test=       nan  train= 0.1088571 
rnd  844: wh-err= 0.999876  th-err= 0.053801  test=       nan  train= 0.1088571 
rnd  845: wh-err= 0.999862  th-err= 0.053793  test=       nan  train= 0.1089286 
rnd  846: wh-err= 0.999835  th-err= 0.053784  test=       nan  train= 0.1085714 
rnd  847: wh-err= 0.999854  th-err= 0.053776  test=       nan  train= 0.1087143 
rnd  848: wh-err= 0.999864  th-err= 0.053769  test=       nan  train= 0.1080000 
rnd  849: wh-err= 0.999859  th-err= 0.053762  test=       nan  train= 0.1081429 
rnd  850: wh-err= 0.999868  th-err= 0.053754  test=       nan  train= 0.1080714 
rnd  851: wh-err= 0.999874  th-err= 0.053748  test=       nan  train= 0.1084286 
rnd  852: wh-err= 0.999869  th-err= 0.053741  test=       nan  train= 0.1084286 
rnd  853: wh-err= 0.999872  th-err= 0.053734  test=       nan  train= 0.1087857 
rnd  854: wh-err= 0.999874  th-err= 0.053727  test=       nan  train= 0.1085714 
rnd  855: wh-err= 0.999875  th-err= 0.053720  test=       nan  train= 0.1087143 
rnd  856: wh-err= 0.999864  th-err= 0.053713  test=       nan  train= 0.1083571 
rnd  857: wh-err= 0.999875  th-err= 0.053706  test=       nan  train= 0.1084286 
rnd  858: wh-err= 0.999869  th-err= 0.053699  test=       nan  train= 0.1087143 
rnd  859: wh-err= 0.999885  th-err= 0.053693  test=       nan  train= 0.1083571 
rnd  860: wh-err= 0.999884  th-err= 0.053687  test=       nan  train= 0.1083571 
rnd  861: wh-err= 0.999876  th-err= 0.053680  test=       nan  train= 0.1083571 
rnd  862: wh-err= 0.999855  th-err= 0.053672  test=       nan  train= 0.1082143 
rnd  863: wh-err= 0.999877  th-err= 0.053666  test=       nan  train= 0.1081429 
rnd  864: wh-err= 0.999887  th-err= 0.053660  test=       nan  train= 0.1082143 
rnd  865: wh-err= 0.999867  th-err= 0.053653  test=       nan  train= 0.1085714 
rnd  866: wh-err= 0.999877  th-err= 0.053646  test=       nan  train= 0.1085714 
rnd  867: wh-err= 0.999907  th-err= 0.053641  test=       nan  train= 0.1085714 
rnd  868: wh-err= 0.999890  th-err= 0.053635  test=       nan  train= 0.1085000 
rnd  869: wh-err= 0.999880  th-err= 0.053629  test=       nan  train= 0.1083571 
rnd  870: wh-err= 0.999887  th-err= 0.053623  test=       nan  train= 0.1085000 
rnd  871: wh-err= 0.999880  th-err= 0.053616  test=       nan  train= 0.1084286 
rnd  872: wh-err= 0.999876  th-err= 0.053610  test=       nan  train= 0.1082857 
rnd  873: wh-err= 0.999880  th-err= 0.053603  test=       nan  train= 0.1085000 
rnd  874: wh-err= 0.999911  th-err= 0.053598  test=       nan  train= 0.1085000 
rnd  875: wh-err= 0.999900  th-err= 0.053593  test=       nan  train= 0.1085714 
rnd  876: wh-err= 0.999892  th-err= 0.053587  test=       nan  train= 0.1085000 
rnd  877: wh-err= 0.999874  th-err= 0.053581  test=       nan  train= 0.1085000 
rnd  878: wh-err= 0.999869  th-err= 0.053574  test=       nan  train= 0.1083571 
rnd  879: wh-err= 0.999847  th-err= 0.053565  test=       nan  train= 0.1084286 
rnd  880: wh-err= 0.999870  th-err= 0.053558  test=       nan  train= 0.1080000 
rnd  881: wh-err= 0.999881  th-err= 0.053552  test=       nan  train= 0.1082857 
rnd  882: wh-err= 0.999893  th-err= 0.053546  test=       nan  train= 0.1084286 
rnd  883: wh-err= 0.999873  th-err= 0.053539  test=       nan  train= 0.1085714 
rnd  884: wh-err= 0.999871  th-err= 0.053533  test=       nan  train= 0.1085714 
rnd  885: wh-err= 0.999873  th-err= 0.053526  test=       nan  train= 0.1085714 
rnd  886: wh-err= 0.999906  th-err= 0.053521  test=       nan  train= 0.1086429 
rnd  887: wh-err= 0.999887  th-err= 0.053515  test=       nan  train= 0.1087857 
rnd  888: wh-err= 0.999894  th-err= 0.053509  test=       nan  train= 0.1088571 
rnd  889: wh-err= 0.999889  th-err= 0.053503  test=       nan  train= 0.1088571 
rnd  890: wh-err= 0.999885  th-err= 0.053497  test=       nan  train= 0.1090000 
rnd  891: wh-err= 0.999885  th-err= 0.053491  test=       nan  train= 0.1087857 
rnd  892: wh-err= 0.999885  th-err= 0.053485  test=       nan  train= 0.1083571 
rnd  893: wh-err= 0.999880  th-err= 0.053478  test=       nan  train= 0.1085000 
rnd  894: wh-err= 0.999911  th-err= 0.053473  test=       nan  train= 0.1085714 
rnd  895: wh-err= 0.999905  th-err= 0.053468  test=       nan  train= 0.1085000 
rnd  896: wh-err= 0.999891  th-err= 0.053463  test=       nan  train= 0.1085714 
rnd  897: wh-err= 0.999886  th-err= 0.053456  test=       nan  train= 0.1083571 
rnd  898: wh-err= 0.999887  th-err= 0.053450  test=       nan  train= 0.1085000 
rnd  899: wh-err= 0.999889  th-err= 0.053444  test=       nan  train= 0.1084286 
rnd  900: wh-err= 0.999922  th-err= 0.053440  test=       nan  train= 0.1084286 
rnd  901: wh-err= 0.999893  th-err= 0.053435  test=       nan  train= 0.1086429 
rnd  902: wh-err= 0.999885  th-err= 0.053428  test=       nan  train= 0.1081429 
rnd  903: wh-err= 0.999884  th-err= 0.053422  test=       nan  train= 0.1080714 
rnd  904: wh-err= 0.999893  th-err= 0.053416  test=       nan  train= 0.1086429 
rnd  905: wh-err= 0.999889  th-err= 0.053411  test=       nan  train= 0.1080714 
rnd  906: wh-err= 0.999893  th-err= 0.053405  test=       nan  train= 0.1077143 
rnd  907: wh-err= 0.999895  th-err= 0.053399  test=       nan  train= 0.1077143 
rnd  908: wh-err= 0.999889  th-err= 0.053393  test=       nan  train= 0.1077857 
rnd  909: wh-err= 0.999880  th-err= 0.053387  test=       nan  train= 0.1077143 
rnd  910: wh-err= 0.999876  th-err= 0.053380  test=       nan  train= 0.1080000 
rnd  911: wh-err= 0.999886  th-err= 0.053374  test=       nan  train= 0.1078571 
rnd  912: wh-err= 0.999885  th-err= 0.053368  test=       nan  train= 0.1078571 
rnd  913: wh-err= 0.999896  th-err= 0.053362  test=       nan  train= 0.1083571 
rnd  914: wh-err= 0.999894  th-err= 0.053357  test=       nan  train= 0.1082857 
rnd  915: wh-err= 0.999879  th-err= 0.053350  test=       nan  train= 0.1079286 
rnd  916: wh-err= 0.999883  th-err= 0.053344  test=       nan  train= 0.1081429 
rnd  917: wh-err= 0.999878  th-err= 0.053337  test=       nan  train= 0.1082857 
rnd  918: wh-err= 0.999893  th-err= 0.053332  test=       nan  train= 0.1082143 
rnd  919: wh-err= 0.999888  th-err= 0.053326  test=       nan  train= 0.1085000 
rnd  920: wh-err= 0.999888  th-err= 0.053320  test=       nan  train= 0.1085000 
rnd  921: wh-err= 0.999889  th-err= 0.053314  test=       nan  train= 0.1082857 
rnd  922: wh-err= 0.999863  th-err= 0.053307  test=       nan  train= 0.1080000 
rnd  923: wh-err= 0.999886  th-err= 0.053301  test=       nan  train= 0.1083571 
rnd  924: wh-err= 0.999889  th-err= 0.053295  test=       nan  train= 0.1084286 
rnd  925: wh-err= 0.999883  th-err= 0.053288  test=       nan  train= 0.1080714 
rnd  926: wh-err= 0.999897  th-err= 0.053283  test=       nan  train= 0.1080714 
rnd  927: wh-err= 0.999897  th-err= 0.053277  test=       nan  train= 0.1079286 
rnd  928: wh-err= 0.999903  th-err= 0.053272  test=       nan  train= 0.1077857 
rnd  929: wh-err= 0.999922  th-err= 0.053268  test=       nan  train= 0.1077857 
rnd  930: wh-err= 0.999905  th-err= 0.053263  test=       nan  train= 0.1076429 
rnd  931: wh-err= 0.999901  th-err= 0.053258  test=       nan  train= 0.1080000 
rnd  932: wh-err= 0.999894  th-err= 0.053252  test=       nan  train= 0.1077857 
rnd  933: wh-err= 0.999885  th-err= 0.053246  test=       nan  train= 0.1082143 
rnd  934: wh-err= 0.999902  th-err= 0.053241  test=       nan  train= 0.1080000 
rnd  935: wh-err= 0.999889  th-err= 0.053235  test=       nan  train= 0.1079286 
rnd  936: wh-err= 0.999903  th-err= 0.053230  test=       nan  train= 0.1078571 
rnd  937: wh-err= 0.999901  th-err= 0.053224  test=       nan  train= 0.1079286 
rnd  938: wh-err= 0.999892  th-err= 0.053219  test=       nan  train= 0.1077857 
rnd  939: wh-err= 0.999889  th-err= 0.053213  test=       nan  train= 0.1077857 
rnd  940: wh-err= 0.999900  th-err= 0.053207  test=       nan  train= 0.1079286 
rnd  941: wh-err= 0.999901  th-err= 0.053202  test=       nan  train= 0.1080000 
rnd  942: wh-err= 0.999893  th-err= 0.053196  test=       nan  train= 0.1080714 
rnd  943: wh-err= 0.999893  th-err= 0.053191  test=       nan  train= 0.1078571 
rnd  944: wh-err= 0.999892  th-err= 0.053185  test=       nan  train= 0.1081429 
rnd  945: wh-err= 0.999897  th-err= 0.053180  test=       nan  train= 0.1081429 
rnd  946: wh-err= 0.999887  th-err= 0.053174  test=       nan  train= 0.1082857 
rnd  947: wh-err= 0.999893  th-err= 0.053168  test=       nan  train= 0.1082857 
rnd  948: wh-err= 0.999895  th-err= 0.053162  test=       nan  train= 0.1080714 
rnd  949: wh-err= 0.999897  th-err= 0.053157  test=       nan  train= 0.1079286 
rnd  950: wh-err= 0.999900  th-err= 0.053152  test=       nan  train= 0.1079286 
rnd  951: wh-err= 0.999902  th-err= 0.053146  test=       nan  train= 0.1082857 
rnd  952: wh-err= 0.999897  th-err= 0.053141  test=       nan  train= 0.1087143 
rnd  953: wh-err= 0.999909  th-err= 0.053136  test=       nan  train= 0.1087857 
rnd  954: wh-err= 0.999865  th-err= 0.053129  test=       nan  train= 0.1089286 
rnd  955: wh-err= 0.999899  th-err= 0.053123  test=       nan  train= 0.1087143 
rnd  956: wh-err= 0.999904  th-err= 0.053118  test=       nan  train= 0.1087143 
rnd  957: wh-err= 0.999915  th-err= 0.053114  test=       nan  train= 0.1087857 
rnd  958: wh-err= 0.999901  th-err= 0.053109  test=       nan  train= 0.1086429 
rnd  959: wh-err= 0.999904  th-err= 0.053103  test=       nan  train= 0.1084286 
rnd  960: wh-err= 0.999893  th-err= 0.053098  test=       nan  train= 0.1084286 
rnd  961: wh-err= 0.999903  th-err= 0.053093  test=       nan  train= 0.1087857 
rnd  962: wh-err= 0.999903  th-err= 0.053088  test=       nan  train= 0.1087143 
rnd  963: wh-err= 0.999903  th-err= 0.053082  test=       nan  train= 0.1085714 
rnd  964: wh-err= 0.999904  th-err= 0.053077  test=       nan  train= 0.1085000 
rnd  965: wh-err= 0.999906  th-err= 0.053072  test=       nan  train= 0.1085000 
rnd  966: wh-err= 0.999914  th-err= 0.053068  test=       nan  train= 0.1084286 
rnd  967: wh-err= 0.999912  th-err= 0.053063  test=       nan  train= 0.1086429 
rnd  968: wh-err= 0.999898  th-err= 0.053058  test=       nan  train= 0.1086429 
rnd  969: wh-err= 0.999913  th-err= 0.053053  test=       nan  train= 0.1087857 
rnd  970: wh-err= 0.999899  th-err= 0.053048  test=       nan  train= 0.1087143 
rnd  971: wh-err= 0.999906  th-err= 0.053043  test=       nan  train= 0.1087143 
rnd  972: wh-err= 0.999909  th-err= 0.053038  test=       nan  train= 0.1083571 
rnd  973: wh-err= 0.999903  th-err= 0.053033  test=       nan  train= 0.1084286 
rnd  974: wh-err= 0.999897  th-err= 0.053027  test=       nan  train= 0.1084286 
rnd  975: wh-err= 0.999912  th-err= 0.053023  test=       nan  train= 0.1082857 
rnd  976: wh-err= 0.999904  th-err= 0.053017  test=       nan  train= 0.1081429 
rnd  977: wh-err= 0.999910  th-err= 0.053013  test=       nan  train= 0.1082857 
rnd  978: wh-err= 0.999904  th-err= 0.053008  test=       nan  train= 0.1077143 
rnd  979: wh-err= 0.999910  th-err= 0.053003  test=       nan  train= 0.1077857 
rnd  980: wh-err= 0.999915  th-err= 0.052998  test=       nan  train= 0.1077857 
rnd  981: wh-err= 0.999904  th-err= 0.052993  test=       nan  train= 0.1075714 
rnd  982: wh-err= 0.999902  th-err= 0.052988  test=       nan  train= 0.1075000 
rnd  983: wh-err= 0.999916  th-err= 0.052984  test=       nan  train= 0.1076429 
rnd  984: wh-err= 0.999921  th-err= 0.052979  test=       nan  train= 0.1077857 
rnd  985: wh-err= 0.999907  th-err= 0.052974  test=       nan  train= 0.1075000 
rnd  986: wh-err= 0.999894  th-err= 0.052969  test=       nan  train= 0.1075000 
rnd  987: wh-err= 0.999902  th-err= 0.052964  test=       nan  train= 0.1074286 
rnd  988: wh-err= 0.999905  th-err= 0.052959  test=       nan  train= 0.1077143 
rnd  989: wh-err= 0.999893  th-err= 0.052953  test=       nan  train= 0.1075000 
rnd  990: wh-err= 0.999893  th-err= 0.052947  test=       nan  train= 0.1074286 
rnd  991: wh-err= 0.999904  th-err= 0.052942  test=       nan  train= 0.1077857 
rnd  992: wh-err= 0.999895  th-err= 0.052937  test=       nan  train= 0.1080714 
rnd  993: wh-err= 0.999891  th-err= 0.052931  test=       nan  train= 0.1082143 
rnd  994: wh-err= 0.999898  th-err= 0.052926  test=       nan  train= 0.1082857 
rnd  995: wh-err= 0.999907  th-err= 0.052921  test=       nan  train= 0.1080714 
rnd  996: wh-err= 0.999879  th-err= 0.052914  test=       nan  train= 0.1080714 
rnd  997: wh-err= 0.999893  th-err= 0.052909  test=       nan  train= 0.1075714 
rnd  998: wh-err= 0.999916  th-err= 0.052904  test=       nan  train= 0.1075000 
rnd  999: wh-err= 0.999910  th-err= 0.052899  test=       nan  train= 0.1075714 
rnd 1000: wh-err= 0.999898  th-err= 0.052894  test=       nan  train= 0.1070714 
=== END program1: ./run learn ../dataset2/train --- OK [153s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 14000.000000 / 14000 = 1.000000
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [2s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s]

===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 6000.000000 / 6000 = 1.000000
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s]


real	2m37.264s
user	2m36.678s
sys	0m0.368s

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