ServerRun 39430
Creatorchuertas
Programboostexter 500r no-awk
DatasetLos tres mosqueteros
Task typeMulticlassClassification
Created2y156d ago
Done! Flag_green
16s
37M
MulticlassClassification
15s
0.056
3s
0.047
1s

Log file

... (lines omitted) ...
rnd  133: wh-err= 0.999373  th-err= 0.293259  test=      -nan  train= 0.0549361 
rnd  134: wh-err= 0.999589  th-err= 0.293138  test=      -nan  train= 0.0549361 
rnd  135: wh-err= 0.999563  th-err= 0.293010  test=      -nan  train= 0.0549361 
rnd  136: wh-err= 0.999643  th-err= 0.292905  test=      -nan  train= 0.0549361 
rnd  137: wh-err= 0.999622  th-err= 0.292795  test=      -nan  train= 0.0549361 
rnd  138: wh-err= 0.999610  th-err= 0.292680  test=      -nan  train= 0.0549361 
rnd  139: wh-err= 0.999789  th-err= 0.292619  test=      -nan  train= 0.0549361 
rnd  140: wh-err= 0.999792  th-err= 0.292558  test=      -nan  train= 0.0549361 
rnd  141: wh-err= 0.999654  th-err= 0.292456  test=      -nan  train= 0.0549361 
rnd  142: wh-err= 0.999794  th-err= 0.292396  test=      -nan  train= 0.0549361 
rnd  143: wh-err= 0.999653  th-err= 0.292295  test=      -nan  train= 0.0549361 
rnd  144: wh-err= 0.999793  th-err= 0.292234  test=      -nan  train= 0.0549361 
rnd  145: wh-err= 0.999660  th-err= 0.292135  test=      -nan  train= 0.0549361 
rnd  146: wh-err= 0.999803  th-err= 0.292077  test=      -nan  train= 0.0549361 
rnd  147: wh-err= 0.999803  th-err= 0.292020  test=      -nan  train= 0.0549361 
rnd  148: wh-err= 0.999804  th-err= 0.291963  test=      -nan  train= 0.0549361 
rnd  149: wh-err= 0.999814  th-err= 0.291908  test=      -nan  train= 0.0549361 
rnd  150: wh-err= 0.999684  th-err= 0.291816  test=      -nan  train= 0.0549361 
rnd  151: wh-err= 0.999686  th-err= 0.291724  test=      -nan  train= 0.0549361 
rnd  152: wh-err= 0.999569  th-err= 0.291599  test=      -nan  train= 0.0552081 
rnd  153: wh-err= 0.999675  th-err= 0.291504  test=      -nan  train= 0.0552081 
rnd  154: wh-err= 0.999622  th-err= 0.291394  test=      -nan  train= 0.0553440 
rnd  155: wh-err= 0.999691  th-err= 0.291304  test=      -nan  train= 0.0553440 
rnd  156: wh-err= 0.999648  th-err= 0.291201  test=      -nan  train= 0.0550721 
rnd  157: wh-err= 0.999835  th-err= 0.291154  test=      -nan  train= 0.0550721 
rnd  158: wh-err= 0.999836  th-err= 0.291106  test=      -nan  train= 0.0550721 
rnd  159: wh-err= 0.999711  th-err= 0.291021  test=      -nan  train= 0.0550721 
rnd  160: wh-err= 0.999701  th-err= 0.290934  test=      -nan  train= 0.0553440 
rnd  161: wh-err= 0.999839  th-err= 0.290888  test=      -nan  train= 0.0553440 
rnd  162: wh-err= 0.999839  th-err= 0.290841  test=      -nan  train= 0.0553440 
rnd  163: wh-err= 0.999720  th-err= 0.290759  test=      -nan  train= 0.0552081 
rnd  164: wh-err= 0.999845  th-err= 0.290714  test=      -nan  train= 0.0553440 
rnd  165: wh-err= 0.999852  th-err= 0.290671  test=      -nan  train= 0.0553440 
rnd  166: wh-err= 0.999853  th-err= 0.290628  test=      -nan  train= 0.0553440 
rnd  167: wh-err= 0.999743  th-err= 0.290553  test=      -nan  train= 0.0552081 
rnd  168: wh-err= 0.999861  th-err= 0.290513  test=      -nan  train= 0.0552081 
rnd  169: wh-err= 0.999862  th-err= 0.290473  test=      -nan  train= 0.0552081 
rnd  170: wh-err= 0.999758  th-err= 0.290403  test=      -nan  train= 0.0552081 
rnd  171: wh-err= 0.999745  th-err= 0.290329  test=      -nan  train= 0.0552081 
rnd  172: wh-err= 0.999735  th-err= 0.290252  test=      -nan  train= 0.0553440 
rnd  173: wh-err= 0.999701  th-err= 0.290165  test=      -nan  train= 0.0553440 
rnd  174: wh-err= 0.999752  th-err= 0.290093  test=      -nan  train= 0.0557520 
rnd  175: wh-err= 0.999875  th-err= 0.290056  test=      -nan  train= 0.0557520 
rnd  176: wh-err= 0.999764  th-err= 0.289988  test=      -nan  train= 0.0557520 
rnd  177: wh-err= 0.999880  th-err= 0.289953  test=      -nan  train= 0.0557520 
rnd  178: wh-err= 0.999774  th-err= 0.289888  test=      -nan  train= 0.0556160 
rnd  179: wh-err= 0.999770  th-err= 0.289821  test=      -nan  train= 0.0556160 
rnd  180: wh-err= 0.999884  th-err= 0.289787  test=      -nan  train= 0.0556160 
rnd  181: wh-err= 0.999781  th-err= 0.289724  test=      -nan  train= 0.0556160 
rnd  182: wh-err= 0.999888  th-err= 0.289691  test=      -nan  train= 0.0556160 
rnd  183: wh-err= 0.999891  th-err= 0.289660  test=      -nan  train= 0.0556160 
rnd  184: wh-err= 0.999786  th-err= 0.289598  test=      -nan  train= 0.0556160 
rnd  185: wh-err= 0.999893  th-err= 0.289567  test=      -nan  train= 0.0556160 
rnd  186: wh-err= 0.999898  th-err= 0.289537  test=      -nan  train= 0.0556160 
rnd  187: wh-err= 0.999799  th-err= 0.289479  test=      -nan  train= 0.0556160 
rnd  188: wh-err= 0.999797  th-err= 0.289421  test=      -nan  train= 0.0554800 
rnd  189: wh-err= 0.999902  th-err= 0.289392  test=      -nan  train= 0.0554800 
rnd  190: wh-err= 0.999903  th-err= 0.289364  test=      -nan  train= 0.0554800 
rnd  191: wh-err= 0.999804  th-err= 0.289307  test=      -nan  train= 0.0554800 
rnd  192: wh-err= 0.999910  th-err= 0.289281  test=      -nan  train= 0.0554800 
rnd  193: wh-err= 0.999911  th-err= 0.289256  test=      -nan  train= 0.0554800 
rnd  194: wh-err= 0.999911  th-err= 0.289230  test=      -nan  train= 0.0554800 
rnd  195: wh-err= 0.999816  th-err= 0.289177  test=      -nan  train= 0.0556160 
rnd  196: wh-err= 0.999910  th-err= 0.289151  test=      -nan  train= 0.0556160 
rnd  197: wh-err= 0.999913  th-err= 0.289126  test=      -nan  train= 0.0556160 
rnd  198: wh-err= 0.999818  th-err= 0.289073  test=      -nan  train= 0.0554800 
rnd  199: wh-err= 0.999793  th-err= 0.289013  test=      -nan  train= 0.0554800 
rnd  200: wh-err= 0.999794  th-err= 0.288954  test=      -nan  train= 0.0554800 
rnd  201: wh-err= 0.999813  th-err= 0.288900  test=      -nan  train= 0.0554800 
rnd  202: wh-err= 0.999810  th-err= 0.288845  test=      -nan  train= 0.0556160 
rnd  203: wh-err= 0.999913  th-err= 0.288820  test=      -nan  train= 0.0556160 
rnd  204: wh-err= 0.999917  th-err= 0.288796  test=      -nan  train= 0.0556160 
rnd  205: wh-err= 0.999923  th-err= 0.288773  test=      -nan  train= 0.0556160 
rnd  206: wh-err= 0.999923  th-err= 0.288751  test=      -nan  train= 0.0556160 
rnd  207: wh-err= 0.999923  th-err= 0.288729  test=      -nan  train= 0.0556160 
rnd  208: wh-err= 0.999840  th-err= 0.288683  test=      -nan  train= 0.0554800 
rnd  209: wh-err= 0.999643  th-err= 0.288579  test=      -nan  train= 0.0556160 
rnd  210: wh-err= 0.999698  th-err= 0.288492  test=      -nan  train= 0.0556160 
rnd  211: wh-err= 0.999738  th-err= 0.288417  test=      -nan  train= 0.0556160 
rnd  212: wh-err= 0.999772  th-err= 0.288351  test=      -nan  train= 0.0556160 
rnd  213: wh-err= 0.999799  th-err= 0.288293  test=      -nan  train= 0.0556160 
rnd  214: wh-err= 0.999823  th-err= 0.288242  test=      -nan  train= 0.0556160 
rnd  215: wh-err= 0.999928  th-err= 0.288221  test=      -nan  train= 0.0556160 
rnd  216: wh-err= 0.999928  th-err= 0.288201  test=      -nan  train= 0.0556160 
rnd  217: wh-err= 0.999841  th-err= 0.288155  test=      -nan  train= 0.0556160 
rnd  218: wh-err= 0.999930  th-err= 0.288135  test=      -nan  train= 0.0556160 
rnd  219: wh-err= 0.999845  th-err= 0.288090  test=      -nan  train= 0.0556160 
rnd  220: wh-err= 0.999931  th-err= 0.288070  test=      -nan  train= 0.0556160 
rnd  221: wh-err= 0.999931  th-err= 0.288050  test=      -nan  train= 0.0556160 
rnd  222: wh-err= 0.999932  th-err= 0.288031  test=      -nan  train= 0.0556160 
rnd  223: wh-err= 0.999934  th-err= 0.288012  test=      -nan  train= 0.0556160 
rnd  224: wh-err= 0.999934  th-err= 0.287993  test=      -nan  train= 0.0556160 
rnd  225: wh-err= 0.999852  th-err= 0.287950  test=      -nan  train= 0.0556160 
rnd  226: wh-err= 0.999935  th-err= 0.287931  test=      -nan  train= 0.0556160 
rnd  227: wh-err= 0.999936  th-err= 0.287913  test=      -nan  train= 0.0556160 
rnd  228: wh-err= 0.999937  th-err= 0.287895  test=      -nan  train= 0.0556160 
rnd  229: wh-err= 0.999937  th-err= 0.287877  test=      -nan  train= 0.0556160 
rnd  230: wh-err= 0.999939  th-err= 0.287859  test=      -nan  train= 0.0556160 
rnd  231: wh-err= 0.999939  th-err= 0.287841  test=      -nan  train= 0.0556160 
rnd  232: wh-err= 0.999941  th-err= 0.287824  test=      -nan  train= 0.0556160 
rnd  233: wh-err= 0.999864  th-err= 0.287785  test=      -nan  train= 0.0556160 
rnd  234: wh-err= 0.999850  th-err= 0.287742  test=      -nan  train= 0.0556160 
rnd  235: wh-err= 0.999852  th-err= 0.287700  test=      -nan  train= 0.0557520 
rnd  236: wh-err= 0.999852  th-err= 0.287657  test=      -nan  train= 0.0557520 
rnd  237: wh-err= 0.999865  th-err= 0.287618  test=      -nan  train= 0.0560239 
rnd  238: wh-err= 0.999846  th-err= 0.287574  test=      -nan  train= 0.0554800 
rnd  239: wh-err= 0.999864  th-err= 0.287535  test=      -nan  train= 0.0557520 
rnd  240: wh-err= 0.999864  th-err= 0.287495  test=      -nan  train= 0.0557520 
rnd  241: wh-err= 0.999670  th-err= 0.287401  test=      -nan  train= 0.0556160 
rnd  242: wh-err= 0.999732  th-err= 0.287324  test=      -nan  train= 0.0557520 
rnd  243: wh-err= 0.999779  th-err= 0.287260  test=      -nan  train= 0.0557520 
rnd  244: wh-err= 0.999814  th-err= 0.287207  test=      -nan  train= 0.0557520 
rnd  245: wh-err= 0.999842  th-err= 0.287161  test=      -nan  train= 0.0557520 
rnd  246: wh-err= 0.999864  th-err= 0.287122  test=      -nan  train= 0.0557520 
rnd  247: wh-err= 0.999943  th-err= 0.287106  test=      -nan  train= 0.0557520 
rnd  248: wh-err= 0.999945  th-err= 0.287090  test=      -nan  train= 0.0557520 
rnd  249: wh-err= 0.999869  th-err= 0.287052  test=      -nan  train= 0.0557520 
rnd  250: wh-err= 0.999848  th-err= 0.287009  test=      -nan  train= 0.0560239 
rnd  251: wh-err= 0.999792  th-err= 0.286949  test=      -nan  train= 0.0561599 
rnd  252: wh-err= 0.999845  th-err= 0.286904  test=      -nan  train= 0.0561599 
rnd  253: wh-err= 0.999869  th-err= 0.286867  test=      -nan  train= 0.0561599 
rnd  254: wh-err= 0.999946  th-err= 0.286851  test=      -nan  train= 0.0561599 
rnd  255: wh-err= 0.999947  th-err= 0.286836  test=      -nan  train= 0.0561599 
rnd  256: wh-err= 0.999948  th-err= 0.286821  test=      -nan  train= 0.0561599 
rnd  257: wh-err= 0.999949  th-err= 0.286806  test=      -nan  train= 0.0561599 
rnd  258: wh-err= 0.999949  th-err= 0.286792  test=      -nan  train= 0.0561599 
rnd  259: wh-err= 0.999950  th-err= 0.286777  test=      -nan  train= 0.0561599 
rnd  260: wh-err= 0.999950  th-err= 0.286763  test=      -nan  train= 0.0561599 
rnd  261: wh-err= 0.999951  th-err= 0.286749  test=      -nan  train= 0.0561599 
rnd  262: wh-err= 0.999880  th-err= 0.286715  test=      -nan  train= 0.0561599 
rnd  263: wh-err= 0.999879  th-err= 0.286680  test=      -nan  train= 0.0561599 
rnd  264: wh-err= 0.999820  th-err= 0.286628  test=      -nan  train= 0.0561599 
rnd  265: wh-err= 0.999952  th-err= 0.286615  test=      -nan  train= 0.0561599 
rnd  266: wh-err= 0.999881  th-err= 0.286580  test=      -nan  train= 0.0561599 
rnd  267: wh-err= 0.999881  th-err= 0.286546  test=      -nan  train= 0.0561599 
rnd  268: wh-err= 0.999953  th-err= 0.286533  test=      -nan  train= 0.0561599 
rnd  269: wh-err= 0.999957  th-err= 0.286521  test=      -nan  train= 0.0561599 
rnd  270: wh-err= 0.999958  th-err= 0.286509  test=      -nan  train= 0.0561599 
rnd  271: wh-err= 0.999959  th-err= 0.286497  test=      -nan  train= 0.0561599 
rnd  272: wh-err= 0.999961  th-err= 0.286486  test=      -nan  train= 0.0561599 
rnd  273: wh-err= 0.999896  th-err= 0.286456  test=      -nan  train= 0.0561599 
rnd  274: wh-err= 0.999884  th-err= 0.286423  test=      -nan  train= 0.0561599 
rnd  275: wh-err= 0.999809  th-err= 0.286368  test=      -nan  train= 0.0561599 
rnd  276: wh-err= 0.999882  th-err= 0.286334  test=      -nan  train= 0.0561599 
rnd  277: wh-err= 0.999846  th-err= 0.286290  test=      -nan  train= 0.0558880 
rnd  278: wh-err= 0.999885  th-err= 0.286257  test=      -nan  train= 0.0558880 
rnd  279: wh-err= 0.999880  th-err= 0.286223  test=      -nan  train= 0.0558880 
rnd  280: wh-err= 0.999962  th-err= 0.286212  test=      -nan  train= 0.0558880 
rnd  281: wh-err= 0.999962  th-err= 0.286201  test=      -nan  train= 0.0558880 
rnd  282: wh-err= 0.999962  th-err= 0.286190  test=      -nan  train= 0.0558880 
rnd  283: wh-err= 0.999899  th-err= 0.286161  test=      -nan  train= 0.0560239 
rnd  284: wh-err= 0.999866  th-err= 0.286123  test=      -nan  train= 0.0557520 
rnd  285: wh-err= 0.999808  th-err= 0.286068  test=      -nan  train= 0.0560239 
rnd  286: wh-err= 0.999856  th-err= 0.286026  test=      -nan  train= 0.0558880 
rnd  287: wh-err= 0.999884  th-err= 0.285993  test=      -nan  train= 0.0558880 
rnd  288: wh-err= 0.999889  th-err= 0.285961  test=      -nan  train= 0.0558880 
rnd  289: wh-err= 0.999896  th-err= 0.285932  test=      -nan  train= 0.0558880 
rnd  290: wh-err= 0.999964  th-err= 0.285921  test=      -nan  train= 0.0558880 
rnd  291: wh-err= 0.999964  th-err= 0.285911  test=      -nan  train= 0.0558880 
rnd  292: wh-err= 0.999964  th-err= 0.285901  test=      -nan  train= 0.0558880 
rnd  293: wh-err= 0.999964  th-err= 0.285891  test=      -nan  train= 0.0558880 
rnd  294: wh-err= 0.999966  th-err= 0.285881  test=      -nan  train= 0.0558880 
rnd  295: wh-err= 0.999966  th-err= 0.285871  test=      -nan  train= 0.0558880 
rnd  296: wh-err= 0.999967  th-err= 0.285862  test=      -nan  train= 0.0558880 
rnd  297: wh-err= 0.999967  th-err= 0.285852  test=      -nan  train= 0.0558880 
rnd  298: wh-err= 0.999968  th-err= 0.285843  test=      -nan  train= 0.0558880 
rnd  299: wh-err= 0.999969  th-err= 0.285834  test=      -nan  train= 0.0558880 
rnd  300: wh-err= 0.999969  th-err= 0.285825  test=      -nan  train= 0.0558880 
rnd  301: wh-err= 0.999969  th-err= 0.285816  test=      -nan  train= 0.0558880 
rnd  302: wh-err= 0.999969  th-err= 0.285808  test=      -nan  train= 0.0558880 
rnd  303: wh-err= 0.999911  th-err= 0.285782  test=      -nan  train= 0.0560239 
rnd  304: wh-err= 0.999971  th-err= 0.285774  test=      -nan  train= 0.0560239 
rnd  305: wh-err= 0.999971  th-err= 0.285765  test=      -nan  train= 0.0560239 
rnd  306: wh-err= 0.999971  th-err= 0.285757  test=      -nan  train= 0.0560239 
rnd  307: wh-err= 0.999971  th-err= 0.285749  test=      -nan  train= 0.0560239 
rnd  308: wh-err= 0.999971  th-err= 0.285741  test=      -nan  train= 0.0560239 
rnd  309: wh-err= 0.999971  th-err= 0.285733  test=      -nan  train= 0.0560239 
rnd  310: wh-err= 0.999971  th-err= 0.285724  test=      -nan  train= 0.0560239 
rnd  311: wh-err= 0.999972  th-err= 0.285716  test=      -nan  train= 0.0560239 
rnd  312: wh-err= 0.999915  th-err= 0.285692  test=      -nan  train= 0.0561599 
rnd  313: wh-err= 0.999914  th-err= 0.285667  test=      -nan  train= 0.0561599 
rnd  314: wh-err= 0.999972  th-err= 0.285659  test=      -nan  train= 0.0561599 
rnd  315: wh-err= 0.999972  th-err= 0.285651  test=      -nan  train= 0.0561599 
rnd  316: wh-err= 0.999972  th-err= 0.285644  test=      -nan  train= 0.0561599 
rnd  317: wh-err= 0.999973  th-err= 0.285636  test=      -nan  train= 0.0561599 
rnd  318: wh-err= 0.999918  th-err= 0.285612  test=      -nan  train= 0.0561599 
rnd  319: wh-err= 0.999973  th-err= 0.285605  test=      -nan  train= 0.0561599 
rnd  320: wh-err= 0.999918  th-err= 0.285581  test=      -nan  train= 0.0564319 
rnd  321: wh-err= 0.999906  th-err= 0.285554  test=      -nan  train= 0.0557520 
rnd  322: wh-err= 0.999913  th-err= 0.285530  test=      -nan  train= 0.0557520 
rnd  323: wh-err= 0.999909  th-err= 0.285504  test=      -nan  train= 0.0557520 
rnd  324: wh-err= 0.999913  th-err= 0.285479  test=      -nan  train= 0.0557520 
rnd  325: wh-err= 0.999918  th-err= 0.285456  test=      -nan  train= 0.0557520 
rnd  326: wh-err= 0.999850  th-err= 0.285413  test=      -nan  train= 0.0558880 
rnd  327: wh-err= 0.999859  th-err= 0.285373  test=      -nan  train= 0.0557520 
rnd  328: wh-err= 0.999892  th-err= 0.285342  test=      -nan  train= 0.0560239 
rnd  329: wh-err= 0.999910  th-err= 0.285316  test=      -nan  train= 0.0557520 
rnd  330: wh-err= 0.999974  th-err= 0.285309  test=      -nan  train= 0.0557520 
rnd  331: wh-err= 0.999975  th-err= 0.285302  test=      -nan  train= 0.0557520 
rnd  332: wh-err= 0.999922  th-err= 0.285280  test=      -nan  train= 0.0560239 
rnd  333: wh-err= 0.999909  th-err= 0.285254  test=      -nan  train= 0.0560239 
rnd  334: wh-err= 0.999921  th-err= 0.285231  test=      -nan  train= 0.0560239 
rnd  335: wh-err= 0.999976  th-err= 0.285224  test=      -nan  train= 0.0560239 
rnd  336: wh-err= 0.999976  th-err= 0.285217  test=      -nan  train= 0.0560239 
rnd  337: wh-err= 0.999924  th-err= 0.285195  test=      -nan  train= 0.0557520 
rnd  338: wh-err= 0.999913  th-err= 0.285171  test=      -nan  train= 0.0557520 
rnd  339: wh-err= 0.999884  th-err= 0.285138  test=      -nan  train= 0.0557520 
rnd  340: wh-err= 0.999869  th-err= 0.285100  test=      -nan  train= 0.0557520 
rnd  341: wh-err= 0.999904  th-err= 0.285073  test=      -nan  train= 0.0558880 
rnd  342: wh-err= 0.999906  th-err= 0.285046  test=      -nan  train= 0.0557520 
rnd  343: wh-err= 0.999919  th-err= 0.285023  test=      -nan  train= 0.0557520 
rnd  344: wh-err= 0.999976  th-err= 0.285016  test=      -nan  train= 0.0557520 
rnd  345: wh-err= 0.999977  th-err= 0.285010  test=      -nan  train= 0.0557520 
rnd  346: wh-err= 0.999977  th-err= 0.285003  test=      -nan  train= 0.0557520 
rnd  347: wh-err= 0.999977  th-err= 0.284997  test=      -nan  train= 0.0557520 
rnd  348: wh-err= 0.999977  th-err= 0.284990  test=      -nan  train= 0.0557520 
rnd  349: wh-err= 0.999928  th-err= 0.284970  test=      -nan  train= 0.0557520 
rnd  350: wh-err= 0.999895  th-err= 0.284939  test=      -nan  train= 0.0557520 
rnd  351: wh-err= 0.999876  th-err= 0.284904  test=      -nan  train= 0.0557520 
rnd  352: wh-err= 0.999902  th-err= 0.284876  test=      -nan  train= 0.0557520 
rnd  353: wh-err= 0.999910  th-err= 0.284851  test=      -nan  train= 0.0557520 
rnd  354: wh-err= 0.999917  th-err= 0.284827  test=      -nan  train= 0.0557520 
rnd  355: wh-err= 0.999914  th-err= 0.284803  test=      -nan  train= 0.0557520 
rnd  356: wh-err= 0.999978  th-err= 0.284796  test=      -nan  train= 0.0557520 
rnd  357: wh-err= 0.999980  th-err= 0.284791  test=      -nan  train= 0.0557520 
rnd  358: wh-err= 0.999980  th-err= 0.284785  test=      -nan  train= 0.0557520 
rnd  359: wh-err= 0.999980  th-err= 0.284779  test=      -nan  train= 0.0557520 
rnd  360: wh-err= 0.999980  th-err= 0.284774  test=      -nan  train= 0.0557520 
rnd  361: wh-err= 0.999981  th-err= 0.284768  test=      -nan  train= 0.0557520 
rnd  362: wh-err= 0.999933  th-err= 0.284749  test=      -nan  train= 0.0557520 
rnd  363: wh-err= 0.999924  th-err= 0.284728  test=      -nan  train= 0.0557520 
rnd  364: wh-err= 0.999925  th-err= 0.284706  test=      -nan  train= 0.0556160 
rnd  365: wh-err= 0.999921  th-err= 0.284684  test=      -nan  train= 0.0557520 
rnd  366: wh-err= 0.999982  th-err= 0.284679  test=      -nan  train= 0.0557520 
rnd  367: wh-err= 0.999982  th-err= 0.284673  test=      -nan  train= 0.0557520 
rnd  368: wh-err= 0.999982  th-err= 0.284668  test=      -nan  train= 0.0557520 
rnd  369: wh-err= 0.999982  th-err= 0.284663  test=      -nan  train= 0.0557520 
rnd  370: wh-err= 0.999982  th-err= 0.284658  test=      -nan  train= 0.0557520 
rnd  371: wh-err= 0.999982  th-err= 0.284653  test=      -nan  train= 0.0557520 
rnd  372: wh-err= 0.999983  th-err= 0.284648  test=      -nan  train= 0.0557520 
rnd  373: wh-err= 0.999983  th-err= 0.284643  test=      -nan  train= 0.0557520 
rnd  374: wh-err= 0.999983  th-err= 0.284638  test=      -nan  train= 0.0557520 
rnd  375: wh-err= 0.999983  th-err= 0.284633  test=      -nan  train= 0.0557520 
rnd  376: wh-err= 0.999983  th-err= 0.284629  test=      -nan  train= 0.0557520 
rnd  377: wh-err= 0.999939  th-err= 0.284611  test=      -nan  train= 0.0557520 
rnd  378: wh-err= 0.999983  th-err= 0.284607  test=      -nan  train= 0.0557520 
rnd  379: wh-err= 0.999984  th-err= 0.284602  test=      -nan  train= 0.0557520 
rnd  380: wh-err= 0.999984  th-err= 0.284597  test=      -nan  train= 0.0557520 
rnd  381: wh-err= 0.999941  th-err= 0.284580  test=      -nan  train= 0.0560239 
rnd  382: wh-err= 0.999904  th-err= 0.284553  test=      -nan  train= 0.0558880 
rnd  383: wh-err= 0.999926  th-err= 0.284532  test=      -nan  train= 0.0557520 
rnd  384: wh-err= 0.999923  th-err= 0.284510  test=      -nan  train= 0.0557520 
rnd  385: wh-err= 0.999917  th-err= 0.284487  test=      -nan  train= 0.0557520 
rnd  386: wh-err= 0.999917  th-err= 0.284463  test=      -nan  train= 0.0557520 
rnd  387: wh-err= 0.999924  th-err= 0.284441  test=      -nan  train= 0.0557520 
rnd  388: wh-err= 0.999930  th-err= 0.284421  test=      -nan  train= 0.0557520 
rnd  389: wh-err= 0.999935  th-err= 0.284403  test=      -nan  train= 0.0557520 
rnd  390: wh-err= 0.999936  th-err= 0.284385  test=      -nan  train= 0.0557520 
rnd  391: wh-err= 0.999903  th-err= 0.284357  test=      -nan  train= 0.0557520 
rnd  392: wh-err= 0.999984  th-err= 0.284353  test=      -nan  train= 0.0557520 
rnd  393: wh-err= 0.999984  th-err= 0.284348  test=      -nan  train= 0.0557520 
rnd  394: wh-err= 0.999984  th-err= 0.284344  test=      -nan  train= 0.0557520 
rnd  395: wh-err= 0.999984  th-err= 0.284339  test=      -nan  train= 0.0557520 
rnd  396: wh-err= 0.999984  th-err= 0.284335  test=      -nan  train= 0.0557520 
rnd  397: wh-err= 0.999942  th-err= 0.284318  test=      -nan  train= 0.0557520 
rnd  398: wh-err= 0.999935  th-err= 0.284300  test=      -nan  train= 0.0557520 
rnd  399: wh-err= 0.999943  th-err= 0.284283  test=      -nan  train= 0.0557520 
rnd  400: wh-err= 0.999985  th-err= 0.284279  test=      -nan  train= 0.0557520 
rnd  401: wh-err= 0.999985  th-err= 0.284275  test=      -nan  train= 0.0557520 
rnd  402: wh-err= 0.999985  th-err= 0.284271  test=      -nan  train= 0.0557520 
rnd  403: wh-err= 0.999985  th-err= 0.284266  test=      -nan  train= 0.0557520 
rnd  404: wh-err= 0.999985  th-err= 0.284262  test=      -nan  train= 0.0557520 
rnd  405: wh-err= 0.999985  th-err= 0.284258  test=      -nan  train= 0.0557520 
rnd  406: wh-err= 0.999985  th-err= 0.284254  test=      -nan  train= 0.0557520 
rnd  407: wh-err= 0.999985  th-err= 0.284250  test=      -nan  train= 0.0557520 
rnd  408: wh-err= 0.999985  th-err= 0.284245  test=      -nan  train= 0.0557520 
rnd  409: wh-err= 0.999985  th-err= 0.284241  test=      -nan  train= 0.0557520 
rnd  410: wh-err= 0.999944  th-err= 0.284225  test=      -nan  train= 0.0557520 
rnd  411: wh-err= 0.999986  th-err= 0.284221  test=      -nan  train= 0.0557520 
rnd  412: wh-err= 0.999986  th-err= 0.284217  test=      -nan  train= 0.0557520 
rnd  413: wh-err= 0.999986  th-err= 0.284213  test=      -nan  train= 0.0557520 
rnd  414: wh-err= 0.999986  th-err= 0.284209  test=      -nan  train= 0.0557520 
rnd  415: wh-err= 0.999986  th-err= 0.284205  test=      -nan  train= 0.0557520 
rnd  416: wh-err= 0.999946  th-err= 0.284190  test=      -nan  train= 0.0557520 
rnd  417: wh-err= 0.999987  th-err= 0.284186  test=      -nan  train= 0.0557520 
rnd  418: wh-err= 0.999987  th-err= 0.284183  test=      -nan  train= 0.0557520 
rnd  419: wh-err= 0.999987  th-err= 0.284179  test=      -nan  train= 0.0557520 
rnd  420: wh-err= 0.999987  th-err= 0.284175  test=      -nan  train= 0.0557520 
rnd  421: wh-err= 0.999949  th-err= 0.284161  test=      -nan  train= 0.0556160 
rnd  422: wh-err= 0.999987  th-err= 0.284157  test=      -nan  train= 0.0556160 
rnd  423: wh-err= 0.999988  th-err= 0.284154  test=      -nan  train= 0.0556160 
rnd  424: wh-err= 0.999988  th-err= 0.284150  test=      -nan  train= 0.0556160 
rnd  425: wh-err= 0.999988  th-err= 0.284147  test=      -nan  train= 0.0556160 
rnd  426: wh-err= 0.999988  th-err= 0.284143  test=      -nan  train= 0.0556160 
rnd  427: wh-err= 0.999952  th-err= 0.284130  test=      -nan  train= 0.0556160 
rnd  428: wh-err= 0.999989  th-err= 0.284126  test=      -nan  train= 0.0556160 
rnd  429: wh-err= 0.999989  th-err= 0.284123  test=      -nan  train= 0.0556160 
rnd  430: wh-err= 0.999989  th-err= 0.284120  test=      -nan  train= 0.0556160 
rnd  431: wh-err= 0.999989  th-err= 0.284117  test=      -nan  train= 0.0556160 
rnd  432: wh-err= 0.999953  th-err= 0.284103  test=      -nan  train= 0.0556160 
rnd  433: wh-err= 0.999946  th-err= 0.284088  test=      -nan  train= 0.0553440 
rnd  434: wh-err= 0.999942  th-err= 0.284072  test=      -nan  train= 0.0556160 
rnd  435: wh-err= 0.999945  th-err= 0.284056  test=      -nan  train= 0.0553440 
rnd  436: wh-err= 0.999948  th-err= 0.284041  test=      -nan  train= 0.0556160 
rnd  437: wh-err= 0.999949  th-err= 0.284027  test=      -nan  train= 0.0553440 
rnd  438: wh-err= 0.999949  th-err= 0.284012  test=      -nan  train= 0.0553440 
rnd  439: wh-err= 0.999937  th-err= 0.283994  test=      -nan  train= 0.0554800 
rnd  440: wh-err= 0.999944  th-err= 0.283978  test=      -nan  train= 0.0554800 
rnd  441: wh-err= 0.999945  th-err= 0.283963  test=      -nan  train= 0.0554800 
rnd  442: wh-err= 0.999934  th-err= 0.283944  test=      -nan  train= 0.0554800 
rnd  443: wh-err= 0.999951  th-err= 0.283930  test=      -nan  train= 0.0554800 
rnd  444: wh-err= 0.999952  th-err= 0.283916  test=      -nan  train= 0.0554800 
rnd  445: wh-err= 0.999947  th-err= 0.283901  test=      -nan  train= 0.0554800 
rnd  446: wh-err= 0.999944  th-err= 0.283885  test=      -nan  train= 0.0554800 
rnd  447: wh-err= 0.999948  th-err= 0.283871  test=      -nan  train= 0.0554800 
rnd  448: wh-err= 0.999931  th-err= 0.283851  test=      -nan  train= 0.0556160 
rnd  449: wh-err= 0.999936  th-err= 0.283833  test=      -nan  train= 0.0556160 
rnd  450: wh-err= 0.999911  th-err= 0.283808  test=      -nan  train= 0.0556160 
rnd  451: wh-err= 0.999918  th-err= 0.283784  test=      -nan  train= 0.0556160 
rnd  452: wh-err= 0.999924  th-err= 0.283763  test=      -nan  train= 0.0556160 
rnd  453: wh-err= 0.999930  th-err= 0.283743  test=      -nan  train= 0.0556160 
rnd  454: wh-err= 0.999934  th-err= 0.283724  test=      -nan  train= 0.0556160 
rnd  455: wh-err= 0.999918  th-err= 0.283701  test=      -nan  train= 0.0556160 
rnd  456: wh-err= 0.999951  th-err= 0.283687  test=      -nan  train= 0.0556160 
rnd  457: wh-err= 0.999989  th-err= 0.283684  test=      -nan  train= 0.0556160 
rnd  458: wh-err= 0.999989  th-err= 0.283681  test=      -nan  train= 0.0556160 
rnd  459: wh-err= 0.999989  th-err= 0.283678  test=      -nan  train= 0.0556160 
rnd  460: wh-err= 0.999989  th-err= 0.283675  test=      -nan  train= 0.0556160 
rnd  461: wh-err= 0.999989  th-err= 0.283672  test=      -nan  train= 0.0556160 
rnd  462: wh-err= 0.999989  th-err= 0.283669  test=      -nan  train= 0.0556160 
rnd  463: wh-err= 0.999990  th-err= 0.283666  test=      -nan  train= 0.0556160 
rnd  464: wh-err= 0.999990  th-err= 0.283663  test=      -nan  train= 0.0556160 
rnd  465: wh-err= 0.999990  th-err= 0.283660  test=      -nan  train= 0.0556160 
rnd  466: wh-err= 0.999990  th-err= 0.283657  test=      -nan  train= 0.0556160 
rnd  467: wh-err= 0.999990  th-err= 0.283655  test=      -nan  train= 0.0556160 
rnd  468: wh-err= 0.999990  th-err= 0.283652  test=      -nan  train= 0.0556160 
rnd  469: wh-err= 0.999990  th-err= 0.283649  test=      -nan  train= 0.0556160 
rnd  470: wh-err= 0.999990  th-err= 0.283646  test=      -nan  train= 0.0556160 
rnd  471: wh-err= 0.999990  th-err= 0.283644  test=      -nan  train= 0.0556160 
rnd  472: wh-err= 0.999956  th-err= 0.283631  test=      -nan  train= 0.0556160 
rnd  473: wh-err= 0.999956  th-err= 0.283619  test=      -nan  train= 0.0556160 
rnd  474: wh-err= 0.999954  th-err= 0.283605  test=      -nan  train= 0.0556160 
rnd  475: wh-err= 0.999945  th-err= 0.283590  test=      -nan  train= 0.0556160 
rnd  476: wh-err= 0.999954  th-err= 0.283577  test=      -nan  train= 0.0556160 
rnd  477: wh-err= 0.999955  th-err= 0.283564  test=      -nan  train= 0.0556160 
rnd  478: wh-err= 0.999954  th-err= 0.283551  test=      -nan  train= 0.0556160 
rnd  479: wh-err= 0.999933  th-err= 0.283532  test=      -nan  train= 0.0556160 
rnd  480: wh-err= 0.999991  th-err= 0.283529  test=      -nan  train= 0.0556160 
rnd  481: wh-err= 0.999991  th-err= 0.283527  test=      -nan  train= 0.0556160 
rnd  482: wh-err= 0.999991  th-err= 0.283524  test=      -nan  train= 0.0556160 
rnd  483: wh-err= 0.999991  th-err= 0.283521  test=      -nan  train= 0.0556160 
rnd  484: wh-err= 0.999991  th-err= 0.283519  test=      -nan  train= 0.0556160 
rnd  485: wh-err= 0.999991  th-err= 0.283516  test=      -nan  train= 0.0556160 
rnd  486: wh-err= 0.999991  th-err= 0.283514  test=      -nan  train= 0.0556160 
rnd  487: wh-err= 0.999991  th-err= 0.283511  test=      -nan  train= 0.0556160 
rnd  488: wh-err= 0.999991  th-err= 0.283509  test=      -nan  train= 0.0556160 
rnd  489: wh-err= 0.999958  th-err= 0.283497  test=      -nan  train= 0.0556160 
rnd  490: wh-err= 0.999991  th-err= 0.283494  test=      -nan  train= 0.0556160 
rnd  491: wh-err= 0.999991  th-err= 0.283491  test=      -nan  train= 0.0556160 
rnd  492: wh-err= 0.999991  th-err= 0.283489  test=      -nan  train= 0.0556160 
rnd  493: wh-err= 0.999991  th-err= 0.283486  test=      -nan  train= 0.0556160 
rnd  494: wh-err= 0.999991  th-err= 0.283484  test=      -nan  train= 0.0556160 
rnd  495: wh-err= 0.999991  th-err= 0.283482  test=      -nan  train= 0.0556160 
rnd  496: wh-err= 0.999991  th-err= 0.283479  test=      -nan  train= 0.0556160 
rnd  497: wh-err= 0.999959  th-err= 0.283468  test=      -nan  train= 0.0556160 
rnd  498: wh-err= 0.999992  th-err= 0.283465  test=      -nan  train= 0.0556160 
rnd  499: wh-err= 0.999992  th-err= 0.283463  test=      -nan  train= 0.0556160 
rnd  500: wh-err= 0.999992  th-err= 0.283461  test=      -nan  train= 0.0556160 
=== END program1: ./run learn ../dataset2/train --- OK [15s]

===== 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 = 7317.000000 / 7354 = 0.994969
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [3s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [0s]

===== 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 = 3131.000000 / 3152 = 0.993338
=== 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 [1s]


real	0m20.396s
user	0m18.461s
sys	0m1.524s

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