ServerRun 39052
Creatorchuertas
Programboostexter 500r no-awk
DatasetOt Products
Task typeMulticlassClassification
Created2y133d ago
Done! Flag_green
4m32s
71M
MulticlassClassification
4m19s
0.216
14s
0.224
6s

Log file

... (lines omitted) ...
rnd  133: wh-err= 0.999175  th-err= 0.230346  test=      -nan  train= 0.2355997 
rnd  134: wh-err= 0.999171  th-err= 0.230155  test=      -nan  train= 0.2356920 
rnd  135: wh-err= 0.999118  th-err= 0.229952  test=      -nan  train= 0.2353457 
rnd  136: wh-err= 0.999152  th-err= 0.229757  test=      -nan  train= 0.2351149 
rnd  137: wh-err= 0.999174  th-err= 0.229568  test=      -nan  train= 0.2347455 
rnd  138: wh-err= 0.999170  th-err= 0.229377  test=      -nan  train= 0.2346531 
rnd  139: wh-err= 0.999200  th-err= 0.229194  test=      -nan  train= 0.2342145 
rnd  140: wh-err= 0.999218  th-err= 0.229014  test=      -nan  train= 0.2337297 
rnd  141: wh-err= 0.999168  th-err= 0.228824  test=      -nan  train= 0.2333834 
rnd  142: wh-err= 0.999205  th-err= 0.228642  test=      -nan  train= 0.2335680 
rnd  143: wh-err= 0.999200  th-err= 0.228459  test=      -nan  train= 0.2335680 
rnd  144: wh-err= 0.999163  th-err= 0.228268  test=      -nan  train= 0.2339143 
rnd  145: wh-err= 0.999234  th-err= 0.228093  test=      -nan  train= 0.2335450 
rnd  146: wh-err= 0.999200  th-err= 0.227910  test=      -nan  train= 0.2328062 
rnd  147: wh-err= 0.999290  th-err= 0.227749  test=      -nan  train= 0.2328524 
rnd  148: wh-err= 0.999328  th-err= 0.227595  test=      -nan  train= 0.2326677 
rnd  149: wh-err= 0.999309  th-err= 0.227438  test=      -nan  train= 0.2322059 
rnd  150: wh-err= 0.999355  th-err= 0.227292  test=      -nan  train= 0.2321828 
rnd  151: wh-err= 0.999322  th-err= 0.227138  test=      -nan  train= 0.2321828 
rnd  152: wh-err= 0.999303  th-err= 0.226979  test=      -nan  train= 0.2322290 
rnd  153: wh-err= 0.999321  th-err= 0.226825  test=      -nan  train= 0.2319751 
rnd  154: wh-err= 0.999301  th-err= 0.226667  test=      -nan  train= 0.2318827 
rnd  155: wh-err= 0.999351  th-err= 0.226520  test=      -nan  train= 0.2317211 
rnd  156: wh-err= 0.999328  th-err= 0.226368  test=      -nan  train= 0.2312132 
rnd  157: wh-err= 0.999345  th-err= 0.226219  test=      -nan  train= 0.2310516 
rnd  158: wh-err= 0.999392  th-err= 0.226082  test=      -nan  train= 0.2313056 
rnd  159: wh-err= 0.999365  th-err= 0.225938  test=      -nan  train= 0.2312132 
rnd  160: wh-err= 0.999316  th-err= 0.225784  test=      -nan  train= 0.2314902 
rnd  161: wh-err= 0.999298  th-err= 0.225625  test=      -nan  train= 0.2315364 
rnd  162: wh-err= 0.999361  th-err= 0.225481  test=      -nan  train= 0.2313748 
rnd  163: wh-err= 0.999343  th-err= 0.225333  test=      -nan  train= 0.2313056 
rnd  164: wh-err= 0.999424  th-err= 0.225203  test=      -nan  train= 0.2311670 
rnd  165: wh-err= 0.999382  th-err= 0.225064  test=      -nan  train= 0.2309593 
rnd  166: wh-err= 0.999367  th-err= 0.224921  test=      -nan  train= 0.2313286 
rnd  167: wh-err= 0.999342  th-err= 0.224773  test=      -nan  train= 0.2315364 
rnd  168: wh-err= 0.999365  th-err= 0.224630  test=      -nan  train= 0.2313748 
rnd  169: wh-err= 0.999365  th-err= 0.224488  test=      -nan  train= 0.2311901 
rnd  170: wh-err= 0.999363  th-err= 0.224345  test=      -nan  train= 0.2309362 
rnd  171: wh-err= 0.999399  th-err= 0.224210  test=      -nan  train= 0.2307976 
rnd  172: wh-err= 0.999385  th-err= 0.224072  test=      -nan  train= 0.2305437 
rnd  173: wh-err= 0.999388  th-err= 0.223935  test=      -nan  train= 0.2307053 
rnd  174: wh-err= 0.999373  th-err= 0.223795  test=      -nan  train= 0.2308207 
rnd  175: wh-err= 0.999409  th-err= 0.223662  test=      -nan  train= 0.2305206 
rnd  176: wh-err= 0.999402  th-err= 0.223529  test=      -nan  train= 0.2301743 
rnd  177: wh-err= 0.999451  th-err= 0.223406  test=      -nan  train= 0.2298742 
rnd  178: wh-err= 0.999496  th-err= 0.223293  test=      -nan  train= 0.2296664 
rnd  179: wh-err= 0.999445  th-err= 0.223170  test=      -nan  train= 0.2295279 
rnd  180: wh-err= 0.999445  th-err= 0.223046  test=      -nan  train= 0.2292970 
rnd  181: wh-err= 0.999445  th-err= 0.222922  test=      -nan  train= 0.2290431 
rnd  182: wh-err= 0.999473  th-err= 0.222804  test=      -nan  train= 0.2286737 
rnd  183: wh-err= 0.999489  th-err= 0.222690  test=      -nan  train= 0.2290200 
rnd  184: wh-err= 0.999434  th-err= 0.222564  test=      -nan  train= 0.2293894 
rnd  185: wh-err= 0.999442  th-err= 0.222440  test=      -nan  train= 0.2290661 
rnd  186: wh-err= 0.999425  th-err= 0.222312  test=      -nan  train= 0.2293894 
rnd  187: wh-err= 0.999454  th-err= 0.222191  test=      -nan  train= 0.2286968 
rnd  188: wh-err= 0.999470  th-err= 0.222073  test=      -nan  train= 0.2286044 
rnd  189: wh-err= 0.999473  th-err= 0.221956  test=      -nan  train= 0.2283505 
rnd  190: wh-err= 0.999485  th-err= 0.221842  test=      -nan  train= 0.2282119 
rnd  191: wh-err= 0.999467  th-err= 0.221723  test=      -nan  train= 0.2284197 
rnd  192: wh-err= 0.999481  th-err= 0.221608  test=      -nan  train= 0.2283274 
rnd  193: wh-err= 0.999518  th-err= 0.221502  test=      -nan  train= 0.2285121 
rnd  194: wh-err= 0.999470  th-err= 0.221384  test=      -nan  train= 0.2285813 
rnd  195: wh-err= 0.999519  th-err= 0.221278  test=      -nan  train= 0.2284197 
rnd  196: wh-err= 0.999399  th-err= 0.221145  test=      -nan  train= 0.2284428 
rnd  197: wh-err= 0.999489  th-err= 0.221032  test=      -nan  train= 0.2278656 
rnd  198: wh-err= 0.999492  th-err= 0.220919  test=      -nan  train= 0.2282350 
rnd  199: wh-err= 0.999507  th-err= 0.220810  test=      -nan  train= 0.2283966 
rnd  200: wh-err= 0.999525  th-err= 0.220705  test=      -nan  train= 0.2282581 
rnd  201: wh-err= 0.999503  th-err= 0.220596  test=      -nan  train= 0.2283966 
rnd  202: wh-err= 0.999502  th-err= 0.220486  test=      -nan  train= 0.2281196 
rnd  203: wh-err= 0.999512  th-err= 0.220378  test=      -nan  train= 0.2280272 
rnd  204: wh-err= 0.999522  th-err= 0.220273  test=      -nan  train= 0.2278195 
rnd  205: wh-err= 0.999527  th-err= 0.220169  test=      -nan  train= 0.2277733 
rnd  206: wh-err= 0.999570  th-err= 0.220074  test=      -nan  train= 0.2277733 
rnd  207: wh-err= 0.999534  th-err= 0.219971  test=      -nan  train= 0.2278425 
rnd  208: wh-err= 0.999509  th-err= 0.219863  test=      -nan  train= 0.2275886 
rnd  209: wh-err= 0.999571  th-err= 0.219769  test=      -nan  train= 0.2272423 
rnd  210: wh-err= 0.999552  th-err= 0.219671  test=      -nan  train= 0.2271269 
rnd  211: wh-err= 0.999555  th-err= 0.219573  test=      -nan  train= 0.2269653 
rnd  212: wh-err= 0.999536  th-err= 0.219471  test=      -nan  train= 0.2271961 
rnd  213: wh-err= 0.999560  th-err= 0.219374  test=      -nan  train= 0.2270345 
rnd  214: wh-err= 0.999537  th-err= 0.219273  test=      -nan  train= 0.2269883 
rnd  215: wh-err= 0.999568  th-err= 0.219178  test=      -nan  train= 0.2271269 
rnd  216: wh-err= 0.999557  th-err= 0.219081  test=      -nan  train= 0.2271730 
rnd  217: wh-err= 0.999615  th-err= 0.218997  test=      -nan  train= 0.2271730 
rnd  218: wh-err= 0.999581  th-err= 0.218905  test=      -nan  train= 0.2271499 
rnd  219: wh-err= 0.999569  th-err= 0.218811  test=      -nan  train= 0.2270345 
rnd  220: wh-err= 0.999564  th-err= 0.218715  test=      -nan  train= 0.2262265 
rnd  221: wh-err= 0.999561  th-err= 0.218619  test=      -nan  train= 0.2264343 
rnd  222: wh-err= 0.999595  th-err= 0.218531  test=      -nan  train= 0.2266882 
rnd  223: wh-err= 0.999589  th-err= 0.218441  test=      -nan  train= 0.2267575 
rnd  224: wh-err= 0.999591  th-err= 0.218352  test=      -nan  train= 0.2266651 
rnd  225: wh-err= 0.999588  th-err= 0.218262  test=      -nan  train= 0.2266420 
rnd  226: wh-err= 0.999593  th-err= 0.218173  test=      -nan  train= 0.2263419 
rnd  227: wh-err= 0.999588  th-err= 0.218083  test=      -nan  train= 0.2264573 
rnd  228: wh-err= 0.999614  th-err= 0.217999  test=      -nan  train= 0.2262034 
rnd  229: wh-err= 0.999580  th-err= 0.217907  test=      -nan  train= 0.2260880 
rnd  230: wh-err= 0.999591  th-err= 0.217818  test=      -nan  train= 0.2262034 
rnd  231: wh-err= 0.999623  th-err= 0.217736  test=      -nan  train= 0.2264343 
rnd  232: wh-err= 0.999620  th-err= 0.217653  test=      -nan  train= 0.2264112 
rnd  233: wh-err= 0.999621  th-err= 0.217571  test=      -nan  train= 0.2262727 
rnd  234: wh-err= 0.999608  th-err= 0.217485  test=      -nan  train= 0.2262496 
rnd  235: wh-err= 0.999630  th-err= 0.217405  test=      -nan  train= 0.2262034 
rnd  236: wh-err= 0.999626  th-err= 0.217324  test=      -nan  train= 0.2262727 
rnd  237: wh-err= 0.999622  th-err= 0.217242  test=      -nan  train= 0.2261572 
rnd  238: wh-err= 0.999616  th-err= 0.217158  test=      -nan  train= 0.2260418 
rnd  239: wh-err= 0.999626  th-err= 0.217077  test=      -nan  train= 0.2258340 
rnd  240: wh-err= 0.999611  th-err= 0.216993  test=      -nan  train= 0.2256724 
rnd  241: wh-err= 0.999612  th-err= 0.216908  test=      -nan  train= 0.2259725 
rnd  242: wh-err= 0.999635  th-err= 0.216829  test=      -nan  train= 0.2259494 
rnd  243: wh-err= 0.999620  th-err= 0.216747  test=      -nan  train= 0.2261572 
rnd  244: wh-err= 0.999617  th-err= 0.216664  test=      -nan  train= 0.2261341 
rnd  245: wh-err= 0.999568  th-err= 0.216570  test=      -nan  train= 0.2259494 
rnd  246: wh-err= 0.999567  th-err= 0.216476  test=      -nan  train= 0.2258802 
rnd  247: wh-err= 0.999612  th-err= 0.216392  test=      -nan  train= 0.2259725 
rnd  248: wh-err= 0.999616  th-err= 0.216309  test=      -nan  train= 0.2258109 
rnd  249: wh-err= 0.999616  th-err= 0.216226  test=      -nan  train= 0.2254184 
rnd  250: wh-err= 0.999634  th-err= 0.216147  test=      -nan  train= 0.2253723 
rnd  251: wh-err= 0.999654  th-err= 0.216072  test=      -nan  train= 0.2252338 
rnd  252: wh-err= 0.999653  th-err= 0.215997  test=      -nan  train= 0.2251414 
rnd  253: wh-err= 0.999640  th-err= 0.215920  test=      -nan  train= 0.2249336 
rnd  254: wh-err= 0.999656  th-err= 0.215845  test=      -nan  train= 0.2247258 
rnd  255: wh-err= 0.999652  th-err= 0.215770  test=      -nan  train= 0.2249105 
rnd  256: wh-err= 0.999642  th-err= 0.215693  test=      -nan  train= 0.2249336 
rnd  257: wh-err= 0.999678  th-err= 0.215624  test=      -nan  train= 0.2250029 
rnd  258: wh-err= 0.999664  th-err= 0.215551  test=      -nan  train= 0.2248875 
rnd  259: wh-err= 0.999658  th-err= 0.215477  test=      -nan  train= 0.2246797 
rnd  260: wh-err= 0.999660  th-err= 0.215404  test=      -nan  train= 0.2246335 
rnd  261: wh-err= 0.999651  th-err= 0.215329  test=      -nan  train= 0.2236639 
rnd  262: wh-err= 0.999630  th-err= 0.215249  test=      -nan  train= 0.2239178 
rnd  263: wh-err= 0.999635  th-err= 0.215171  test=      -nan  train= 0.2243334 
rnd  264: wh-err= 0.999678  th-err= 0.215101  test=      -nan  train= 0.2245181 
rnd  265: wh-err= 0.999676  th-err= 0.215032  test=      -nan  train= 0.2240332 
rnd  266: wh-err= 0.999660  th-err= 0.214959  test=      -nan  train= 0.2242179 
rnd  267: wh-err= 0.999679  th-err= 0.214890  test=      -nan  train= 0.2241949 
rnd  268: wh-err= 0.999706  th-err= 0.214826  test=      -nan  train= 0.2241256 
rnd  269: wh-err= 0.999688  th-err= 0.214759  test=      -nan  train= 0.2240332 
rnd  270: wh-err= 0.999678  th-err= 0.214690  test=      -nan  train= 0.2235946 
rnd  271: wh-err= 0.999696  th-err= 0.214625  test=      -nan  train= 0.2240332 
rnd  272: wh-err= 0.999685  th-err= 0.214557  test=      -nan  train= 0.2242410 
rnd  273: wh-err= 0.999683  th-err= 0.214489  test=      -nan  train= 0.2240102 
rnd  274: wh-err= 0.999683  th-err= 0.214421  test=      -nan  train= 0.2241256 
rnd  275: wh-err= 0.999681  th-err= 0.214353  test=      -nan  train= 0.2240563 
rnd  276: wh-err= 0.999687  th-err= 0.214286  test=      -nan  train= 0.2240102 
rnd  277: wh-err= 0.999662  th-err= 0.214213  test=      -nan  train= 0.2240563 
rnd  278: wh-err= 0.999688  th-err= 0.214147  test=      -nan  train= 0.2241025 
rnd  279: wh-err= 0.999684  th-err= 0.214079  test=      -nan  train= 0.2241949 
rnd  280: wh-err= 0.999638  th-err= 0.214002  test=      -nan  train= 0.2239409 
rnd  281: wh-err= 0.999685  th-err= 0.213934  test=      -nan  train= 0.2241718 
rnd  282: wh-err= 0.999711  th-err= 0.213872  test=      -nan  train= 0.2241256 
rnd  283: wh-err= 0.999637  th-err= 0.213795  test=      -nan  train= 0.2244719 
rnd  284: wh-err= 0.999710  th-err= 0.213733  test=      -nan  train= 0.2242641 
rnd  285: wh-err= 0.999700  th-err= 0.213669  test=      -nan  train= 0.2239871 
rnd  286: wh-err= 0.999694  th-err= 0.213603  test=      -nan  train= 0.2240332 
rnd  287: wh-err= 0.999685  th-err= 0.213536  test=      -nan  train= 0.2239409 
rnd  288: wh-err= 0.999703  th-err= 0.213473  test=      -nan  train= 0.2240332 
rnd  289: wh-err= 0.999697  th-err= 0.213408  test=      -nan  train= 0.2239640 
rnd  290: wh-err= 0.999701  th-err= 0.213344  test=      -nan  train= 0.2235023 
rnd  291: wh-err= 0.999706  th-err= 0.213281  test=      -nan  train= 0.2237331 
rnd  292: wh-err= 0.999715  th-err= 0.213220  test=      -nan  train= 0.2238255 
rnd  293: wh-err= 0.999687  th-err= 0.213154  test=      -nan  train= 0.2236869 
rnd  294: wh-err= 0.999702  th-err= 0.213090  test=      -nan  train= 0.2238024 
rnd  295: wh-err= 0.999687  th-err= 0.213024  test=      -nan  train= 0.2236177 
rnd  296: wh-err= 0.999695  th-err= 0.212958  test=      -nan  train= 0.2238255 
rnd  297: wh-err= 0.999699  th-err= 0.212894  test=      -nan  train= 0.2235946 
rnd  298: wh-err= 0.999714  th-err= 0.212833  test=      -nan  train= 0.2235484 
rnd  299: wh-err= 0.999713  th-err= 0.212772  test=      -nan  train= 0.2233637 
rnd  300: wh-err= 0.999697  th-err= 0.212708  test=      -nan  train= 0.2223479 
rnd  301: wh-err= 0.999708  th-err= 0.212646  test=      -nan  train= 0.2222787 
rnd  302: wh-err= 0.999719  th-err= 0.212586  test=      -nan  train= 0.2220940 
rnd  303: wh-err= 0.999713  th-err= 0.212525  test=      -nan  train= 0.2219324 
rnd  304: wh-err= 0.999723  th-err= 0.212466  test=      -nan  train= 0.2219324 
rnd  305: wh-err= 0.999726  th-err= 0.212408  test=      -nan  train= 0.2219093 
rnd  306: wh-err= 0.999710  th-err= 0.212346  test=      -nan  train= 0.2219324 
rnd  307: wh-err= 0.999708  th-err= 0.212284  test=      -nan  train= 0.2221401 
rnd  308: wh-err= 0.999723  th-err= 0.212226  test=      -nan  train= 0.2217246 
rnd  309: wh-err= 0.999717  th-err= 0.212166  test=      -nan  train= 0.2220478 
rnd  310: wh-err= 0.999730  th-err= 0.212108  test=      -nan  train= 0.2220478 
rnd  311: wh-err= 0.999723  th-err= 0.212050  test=      -nan  train= 0.2218631 
rnd  312: wh-err= 0.999710  th-err= 0.211988  test=      -nan  train= 0.2219554 
rnd  313: wh-err= 0.999731  th-err= 0.211931  test=      -nan  train= 0.2217477 
rnd  314: wh-err= 0.999747  th-err= 0.211877  test=      -nan  train= 0.2218631 
rnd  315: wh-err= 0.999751  th-err= 0.211825  test=      -nan  train= 0.2217707 
rnd  316: wh-err= 0.999737  th-err= 0.211769  test=      -nan  train= 0.2217246 
rnd  317: wh-err= 0.999723  th-err= 0.211710  test=      -nan  train= 0.2217707 
rnd  318: wh-err= 0.999734  th-err= 0.211654  test=      -nan  train= 0.2214014 
rnd  319: wh-err= 0.999737  th-err= 0.211598  test=      -nan  train= 0.2211474 
rnd  320: wh-err= 0.999741  th-err= 0.211543  test=      -nan  train= 0.2211705 
rnd  321: wh-err= 0.999740  th-err= 0.211488  test=      -nan  train= 0.2212398 
rnd  322: wh-err= 0.999676  th-err= 0.211420  test=      -nan  train= 0.2211012 
rnd  323: wh-err= 0.999746  th-err= 0.211366  test=      -nan  train= 0.2210320 
rnd  324: wh-err= 0.999759  th-err= 0.211315  test=      -nan  train= 0.2209858 
rnd  325: wh-err= 0.999740  th-err= 0.211260  test=      -nan  train= 0.2209396 
rnd  326: wh-err= 0.999725  th-err= 0.211202  test=      -nan  train= 0.2209627 
rnd  327: wh-err= 0.999732  th-err= 0.211145  test=      -nan  train= 0.2211474 
rnd  328: wh-err= 0.999756  th-err= 0.211094  test=      -nan  train= 0.2210551 
rnd  329: wh-err= 0.999755  th-err= 0.211042  test=      -nan  train= 0.2208473 
rnd  330: wh-err= 0.999774  th-err= 0.210994  test=      -nan  train= 0.2208704 
rnd  331: wh-err= 0.999755  th-err= 0.210943  test=      -nan  train= 0.2210089 
rnd  332: wh-err= 0.999701  th-err= 0.210879  test=      -nan  train= 0.2210551 
rnd  333: wh-err= 0.999753  th-err= 0.210827  test=      -nan  train= 0.2209396 
rnd  334: wh-err= 0.999741  th-err= 0.210773  test=      -nan  train= 0.2208704 
rnd  335: wh-err= 0.999752  th-err= 0.210720  test=      -nan  train= 0.2209396 
rnd  336: wh-err= 0.999752  th-err= 0.210668  test=      -nan  train= 0.2208704 
rnd  337: wh-err= 0.999754  th-err= 0.210616  test=      -nan  train= 0.2210320 
rnd  338: wh-err= 0.999755  th-err= 0.210565  test=      -nan  train= 0.2211012 
rnd  339: wh-err= 0.999758  th-err= 0.210514  test=      -nan  train= 0.2209396 
rnd  340: wh-err= 0.999755  th-err= 0.210462  test=      -nan  train= 0.2206395 
rnd  341: wh-err= 0.999771  th-err= 0.210414  test=      -nan  train= 0.2206626 
rnd  342: wh-err= 0.999761  th-err= 0.210364  test=      -nan  train= 0.2203394 
rnd  343: wh-err= 0.999757  th-err= 0.210312  test=      -nan  train= 0.2203625 
rnd  344: wh-err= 0.999758  th-err= 0.210262  test=      -nan  train= 0.2202009 
rnd  345: wh-err= 0.999782  th-err= 0.210216  test=      -nan  train= 0.2203394 
rnd  346: wh-err= 0.999758  th-err= 0.210165  test=      -nan  train= 0.2199931 
rnd  347: wh-err= 0.999726  th-err= 0.210107  test=      -nan  train= 0.2201778 
rnd  348: wh-err= 0.999763  th-err= 0.210058  test=      -nan  train= 0.2199238 
rnd  349: wh-err= 0.999759  th-err= 0.210007  test=      -nan  train= 0.2198776 
rnd  350: wh-err= 0.999784  th-err= 0.209962  test=      -nan  train= 0.2197160 
rnd  351: wh-err= 0.999767  th-err= 0.209913  test=      -nan  train= 0.2196006 
rnd  352: wh-err= 0.999776  th-err= 0.209866  test=      -nan  train= 0.2198084 
rnd  353: wh-err= 0.999773  th-err= 0.209818  test=      -nan  train= 0.2199238 
rnd  354: wh-err= 0.999767  th-err= 0.209769  test=      -nan  train= 0.2197622 
rnd  355: wh-err= 0.999763  th-err= 0.209720  test=      -nan  train= 0.2197853 
rnd  356: wh-err= 0.999770  th-err= 0.209672  test=      -nan  train= 0.2195775 
rnd  357: wh-err= 0.999772  th-err= 0.209624  test=      -nan  train= 0.2195775 
rnd  358: wh-err= 0.999775  th-err= 0.209577  test=      -nan  train= 0.2196237 
rnd  359: wh-err= 0.999776  th-err= 0.209530  test=      -nan  train= 0.2195775 
rnd  360: wh-err= 0.999771  th-err= 0.209482  test=      -nan  train= 0.2195544 
rnd  361: wh-err= 0.999776  th-err= 0.209435  test=      -nan  train= 0.2192312 
rnd  362: wh-err= 0.999771  th-err= 0.209387  test=      -nan  train= 0.2191620 
rnd  363: wh-err= 0.999802  th-err= 0.209346  test=      -nan  train= 0.2194390 
rnd  364: wh-err= 0.999781  th-err= 0.209300  test=      -nan  train= 0.2188157 
rnd  365: wh-err= 0.999783  th-err= 0.209254  test=      -nan  train= 0.2186310 
rnd  366: wh-err= 0.999780  th-err= 0.209208  test=      -nan  train= 0.2185848 
rnd  367: wh-err= 0.999794  th-err= 0.209165  test=      -nan  train= 0.2185155 
rnd  368: wh-err= 0.999772  th-err= 0.209117  test=      -nan  train= 0.2187233 
rnd  369: wh-err= 0.999782  th-err= 0.209072  test=      -nan  train= 0.2186310 
rnd  370: wh-err= 0.999783  th-err= 0.209026  test=      -nan  train= 0.2184924 
rnd  371: wh-err= 0.999786  th-err= 0.208981  test=      -nan  train= 0.2185617 
rnd  372: wh-err= 0.999790  th-err= 0.208938  test=      -nan  train= 0.2187464 
rnd  373: wh-err= 0.999792  th-err= 0.208894  test=      -nan  train= 0.2190465 
rnd  374: wh-err= 0.999786  th-err= 0.208849  test=      -nan  train= 0.2188849 
rnd  375: wh-err= 0.999762  th-err= 0.208800  test=      -nan  train= 0.2187002 
rnd  376: wh-err= 0.999785  th-err= 0.208755  test=      -nan  train= 0.2190003 
rnd  377: wh-err= 0.999777  th-err= 0.208708  test=      -nan  train= 0.2187464 
rnd  378: wh-err= 0.999786  th-err= 0.208664  test=      -nan  train= 0.2188849 
rnd  379: wh-err= 0.999768  th-err= 0.208615  test=      -nan  train= 0.2188157 
rnd  380: wh-err= 0.999792  th-err= 0.208572  test=      -nan  train= 0.2186079 
rnd  381: wh-err= 0.999796  th-err= 0.208529  test=      -nan  train= 0.2187926 
rnd  382: wh-err= 0.999794  th-err= 0.208486  test=      -nan  train= 0.2189311 
rnd  383: wh-err= 0.999791  th-err= 0.208443  test=      -nan  train= 0.2187464 
rnd  384: wh-err= 0.999744  th-err= 0.208389  test=      -nan  train= 0.2188849 
rnd  385: wh-err= 0.999794  th-err= 0.208347  test=      -nan  train= 0.2190696 
rnd  386: wh-err= 0.999809  th-err= 0.208307  test=      -nan  train= 0.2189773 
rnd  387: wh-err= 0.999796  th-err= 0.208264  test=      -nan  train= 0.2189080 
rnd  388: wh-err= 0.999826  th-err= 0.208228  test=      -nan  train= 0.2187464 
rnd  389: wh-err= 0.999817  th-err= 0.208190  test=      -nan  train= 0.2187002 
rnd  390: wh-err= 0.999824  th-err= 0.208153  test=      -nan  train= 0.2186540 
rnd  391: wh-err= 0.999823  th-err= 0.208116  test=      -nan  train= 0.2186771 
rnd  392: wh-err= 0.999807  th-err= 0.208076  test=      -nan  train= 0.2186310 
rnd  393: wh-err= 0.999803  th-err= 0.208035  test=      -nan  train= 0.2184924 
rnd  394: wh-err= 0.999773  th-err= 0.207988  test=      -nan  train= 0.2184463 
rnd  395: wh-err= 0.999808  th-err= 0.207948  test=      -nan  train= 0.2183770 
rnd  396: wh-err= 0.999807  th-err= 0.207908  test=      -nan  train= 0.2183770 
rnd  397: wh-err= 0.999811  th-err= 0.207869  test=      -nan  train= 0.2183539 
rnd  398: wh-err= 0.999808  th-err= 0.207829  test=      -nan  train= 0.2182847 
rnd  399: wh-err= 0.999809  th-err= 0.207789  test=      -nan  train= 0.2178691 
rnd  400: wh-err= 0.999806  th-err= 0.207749  test=      -nan  train= 0.2178460 
rnd  401: wh-err= 0.999803  th-err= 0.207708  test=      -nan  train= 0.2178229 
rnd  402: wh-err= 0.999815  th-err= 0.207670  test=      -nan  train= 0.2177998 
rnd  403: wh-err= 0.999782  th-err= 0.207624  test=      -nan  train= 0.2179153 
rnd  404: wh-err= 0.999788  th-err= 0.207580  test=      -nan  train= 0.2178691 
rnd  405: wh-err= 0.999813  th-err= 0.207541  test=      -nan  train= 0.2178691 
rnd  406: wh-err= 0.999802  th-err= 0.207500  test=      -nan  train= 0.2177537 
rnd  407: wh-err= 0.999802  th-err= 0.207459  test=      -nan  train= 0.2176844 
rnd  408: wh-err= 0.999803  th-err= 0.207418  test=      -nan  train= 0.2177537 
rnd  409: wh-err= 0.999808  th-err= 0.207379  test=      -nan  train= 0.2176382 
rnd  410: wh-err= 0.999817  th-err= 0.207341  test=      -nan  train= 0.2174766 
rnd  411: wh-err= 0.999809  th-err= 0.207301  test=      -nan  train= 0.2174997 
rnd  412: wh-err= 0.999821  th-err= 0.207264  test=      -nan  train= 0.2173150 
rnd  413: wh-err= 0.999810  th-err= 0.207224  test=      -nan  train= 0.2173381 
rnd  414: wh-err= 0.999813  th-err= 0.207186  test=      -nan  train= 0.2173843 
rnd  415: wh-err= 0.999807  th-err= 0.207146  test=      -nan  train= 0.2171996 
rnd  416: wh-err= 0.999817  th-err= 0.207108  test=      -nan  train= 0.2172458 
rnd  417: wh-err= 0.999835  th-err= 0.207074  test=      -nan  train= 0.2172688 
rnd  418: wh-err= 0.999819  th-err= 0.207036  test=      -nan  train= 0.2173150 
rnd  419: wh-err= 0.999812  th-err= 0.206997  test=      -nan  train= 0.2171996 
rnd  420: wh-err= 0.999798  th-err= 0.206955  test=      -nan  train= 0.2169918 
rnd  421: wh-err= 0.999809  th-err= 0.206916  test=      -nan  train= 0.2169456 
rnd  422: wh-err= 0.999802  th-err= 0.206875  test=      -nan  train= 0.2168302 
rnd  423: wh-err= 0.999822  th-err= 0.206838  test=      -nan  train= 0.2168764 
rnd  424: wh-err= 0.999832  th-err= 0.206803  test=      -nan  train= 0.2167840 
rnd  425: wh-err= 0.999828  th-err= 0.206768  test=      -nan  train= 0.2168764 
rnd  426: wh-err= 0.999833  th-err= 0.206733  test=      -nan  train= 0.2170149 
rnd  427: wh-err= 0.999819  th-err= 0.206696  test=      -nan  train= 0.2173612 
rnd  428: wh-err= 0.999780  th-err= 0.206650  test=      -nan  train= 0.2172688 
rnd  429: wh-err= 0.999817  th-err= 0.206613  test=      -nan  train= 0.2174997 
rnd  430: wh-err= 0.999810  th-err= 0.206573  test=      -nan  train= 0.2173381 
rnd  431: wh-err= 0.999816  th-err= 0.206535  test=      -nan  train= 0.2173150 
rnd  432: wh-err= 0.999829  th-err= 0.206500  test=      -nan  train= 0.2171072 
rnd  433: wh-err= 0.999810  th-err= 0.206461  test=      -nan  train= 0.2171765 
rnd  434: wh-err= 0.999812  th-err= 0.206422  test=      -nan  train= 0.2173843 
rnd  435: wh-err= 0.999811  th-err= 0.206383  test=      -nan  train= 0.2172688 
rnd  436: wh-err= 0.999807  th-err= 0.206343  test=      -nan  train= 0.2171996 
rnd  437: wh-err= 0.999813  th-err= 0.206304  test=      -nan  train= 0.2170842 
rnd  438: wh-err= 0.999817  th-err= 0.206267  test=      -nan  train= 0.2171303 
rnd  439: wh-err= 0.999805  th-err= 0.206226  test=      -nan  train= 0.2172458 
rnd  440: wh-err= 0.999815  th-err= 0.206188  test=      -nan  train= 0.2171765 
rnd  441: wh-err= 0.999826  th-err= 0.206153  test=      -nan  train= 0.2172688 
rnd  442: wh-err= 0.999828  th-err= 0.206117  test=      -nan  train= 0.2171996 
rnd  443: wh-err= 0.999829  th-err= 0.206082  test=      -nan  train= 0.2171534 
rnd  444: wh-err= 0.999817  th-err= 0.206044  test=      -nan  train= 0.2171534 
rnd  445: wh-err= 0.999735  th-err= 0.205990  test=      -nan  train= 0.2170611 
rnd  446: wh-err= 0.999809  th-err= 0.205950  test=      -nan  train= 0.2171072 
rnd  447: wh-err= 0.999805  th-err= 0.205910  test=      -nan  train= 0.2170842 
rnd  448: wh-err= 0.999836  th-err= 0.205876  test=      -nan  train= 0.2171303 
rnd  449: wh-err= 0.999781  th-err= 0.205831  test=      -nan  train= 0.2170380 
rnd  450: wh-err= 0.999820  th-err= 0.205794  test=      -nan  train= 0.2169687 
rnd  451: wh-err= 0.999834  th-err= 0.205760  test=      -nan  train= 0.2168533 
rnd  452: wh-err= 0.999835  th-err= 0.205726  test=      -nan  train= 0.2170611 
rnd  453: wh-err= 0.999835  th-err= 0.205692  test=      -nan  train= 0.2169918 
rnd  454: wh-err= 0.999812  th-err= 0.205653  test=      -nan  train= 0.2170380 
rnd  455: wh-err= 0.999816  th-err= 0.205616  test=      -nan  train= 0.2170380 
rnd  456: wh-err= 0.999829  th-err= 0.205581  test=      -nan  train= 0.2170842 
rnd  457: wh-err= 0.999836  th-err= 0.205547  test=      -nan  train= 0.2170149 
rnd  458: wh-err= 0.999842  th-err= 0.205514  test=      -nan  train= 0.2169687 
rnd  459: wh-err= 0.999845  th-err= 0.205482  test=      -nan  train= 0.2169687 
rnd  460: wh-err= 0.999785  th-err= 0.205438  test=      -nan  train= 0.2169687 
rnd  461: wh-err= 0.999833  th-err= 0.205404  test=      -nan  train= 0.2171996 
rnd  462: wh-err= 0.999828  th-err= 0.205369  test=      -nan  train= 0.2171303 
rnd  463: wh-err= 0.999825  th-err= 0.205333  test=      -nan  train= 0.2168764 
rnd  464: wh-err= 0.999828  th-err= 0.205297  test=      -nan  train= 0.2170380 
rnd  465: wh-err= 0.999834  th-err= 0.205263  test=      -nan  train= 0.2167840 
rnd  466: wh-err= 0.999838  th-err= 0.205230  test=      -nan  train= 0.2164377 
rnd  467: wh-err= 0.999778  th-err= 0.205184  test=      -nan  train= 0.2165993 
rnd  468: wh-err= 0.999841  th-err= 0.205152  test=      -nan  train= 0.2165301 
rnd  469: wh-err= 0.999850  th-err= 0.205121  test=      -nan  train= 0.2164608 
rnd  470: wh-err= 0.999848  th-err= 0.205090  test=      -nan  train= 0.2165532 
rnd  471: wh-err= 0.999839  th-err= 0.205057  test=      -nan  train= 0.2165993 
rnd  472: wh-err= 0.999850  th-err= 0.205026  test=      -nan  train= 0.2163685 
rnd  473: wh-err= 0.999750  th-err= 0.204975  test=      -nan  train= 0.2162761 
rnd  474: wh-err= 0.999795  th-err= 0.204933  test=      -nan  train= 0.2164377 
rnd  475: wh-err= 0.999847  th-err= 0.204901  test=      -nan  train= 0.2163454 
rnd  476: wh-err= 0.999835  th-err= 0.204867  test=      -nan  train= 0.2165070 
rnd  477: wh-err= 0.999847  th-err= 0.204836  test=      -nan  train= 0.2165301 
rnd  478: wh-err= 0.999839  th-err= 0.204803  test=      -nan  train= 0.2165993 
rnd  479: wh-err= 0.999834  th-err= 0.204769  test=      -nan  train= 0.2166455 
rnd  480: wh-err= 0.999831  th-err= 0.204735  test=      -nan  train= 0.2163454 
rnd  481: wh-err= 0.999846  th-err= 0.204703  test=      -nan  train= 0.2166686 
rnd  482: wh-err= 0.999842  th-err= 0.204671  test=      -nan  train= 0.2163454 
rnd  483: wh-err= 0.999829  th-err= 0.204636  test=      -nan  train= 0.2164839 
rnd  484: wh-err= 0.999836  th-err= 0.204602  test=      -nan  train= 0.2166224 
rnd  485: wh-err= 0.999842  th-err= 0.204570  test=      -nan  train= 0.2165301 
rnd  486: wh-err= 0.999848  th-err= 0.204539  test=      -nan  train= 0.2165301 
rnd  487: wh-err= 0.999852  th-err= 0.204508  test=      -nan  train= 0.2165070 
rnd  488: wh-err= 0.999850  th-err= 0.204478  test=      -nan  train= 0.2159298 
rnd  489: wh-err= 0.999841  th-err= 0.204445  test=      -nan  train= 0.2162992 
rnd  490: wh-err= 0.999846  th-err= 0.204414  test=      -nan  train= 0.2164839 
rnd  491: wh-err= 0.999848  th-err= 0.204383  test=      -nan  train= 0.2164377 
rnd  492: wh-err= 0.999864  th-err= 0.204355  test=      -nan  train= 0.2163223 
rnd  493: wh-err= 0.999860  th-err= 0.204326  test=      -nan  train= 0.2162530 
rnd  494: wh-err= 0.999853  th-err= 0.204296  test=      -nan  train= 0.2164608 
rnd  495: wh-err= 0.999866  th-err= 0.204269  test=      -nan  train= 0.2163223 
rnd  496: wh-err= 0.999840  th-err= 0.204236  test=      -nan  train= 0.2162761 
rnd  497: wh-err= 0.999853  th-err= 0.204206  test=      -nan  train= 0.2163454 
rnd  498: wh-err= 0.999851  th-err= 0.204175  test=      -nan  train= 0.2164608 
rnd  499: wh-err= 0.999853  th-err= 0.204145  test=      -nan  train= 0.2163223 
rnd  500: wh-err= 0.999875  th-err= 0.204120  test=      -nan  train= 0.2164146 
=== END program1: ./run learn ../dataset2/train --- OK [259s]

===== 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 [1s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 42396.000000 / 43315 = 0.978783
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [14s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [2s]

===== 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 [1s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 18214.000000 / 18563 = 0.981199
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [6s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s]


real	4m43.855s
user	4m34.297s
sys	0m4.856s

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