ServerRun 38748
Creatorchuertas
Programboostexter no-awk
DatasetVirus 183,855x9 00-FF w/Chi2 (Small Train)
Task typeMulticlassClassification
Created2y224d ago
Done! Flag_green
55m52s
269M
MulticlassClassification
53m37s
0
32s
0.010
1m14s

Log file

... (lines omitted) ...
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rnd  854: wh-err= 0.937219  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  855: wh-err= 0.918369  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  856: wh-err= 0.936099  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  857: wh-err= 0.933790  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  858: wh-err= 0.936582  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  859: wh-err= 0.942918  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  860: wh-err= 0.942200  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  861: wh-err= 0.942159  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  862: wh-err= 0.947230  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  863: wh-err= 0.940915  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  864: wh-err= 0.941609  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  865: wh-err= 0.942063  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  866: wh-err= 0.941758  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  867: wh-err= 0.936986  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  868: wh-err= 0.935826  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  869: wh-err= 0.932403  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  870: wh-err= 0.932931  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  871: wh-err= 0.911746  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  872: wh-err= 0.927445  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  873: wh-err= 0.929987  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  874: wh-err= 0.923195  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  875: wh-err= 0.927436  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  876: wh-err= 0.935367  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  877: wh-err= 0.935422  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  878: wh-err= 0.925168  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  879: wh-err= 0.928810  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  880: wh-err= 0.921679  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  881: wh-err= 0.933061  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  882: wh-err= 0.935710  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  883: wh-err= 0.926208  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  884: wh-err= 0.921838  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  885: wh-err= 0.936822  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  886: wh-err= 0.939812  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  887: wh-err= 0.936039  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  888: wh-err= 0.935023  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  889: wh-err= 0.941359  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  890: wh-err= 0.935925  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  891: wh-err= 0.940024  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  892: wh-err= 0.944292  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  893: wh-err= 0.933163  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  894: wh-err= 0.935571  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  895: wh-err= 0.921875  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  896: wh-err= 0.933115  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  897: wh-err= 0.939325  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  898: wh-err= 0.939768  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  899: wh-err= 0.929050  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  900: wh-err= 0.941209  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  901: wh-err= 0.940390  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  902: wh-err= 0.923766  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  903: wh-err= 0.928570  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  904: wh-err= 0.927701  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  905: wh-err= 0.930604  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  906: wh-err= 0.930701  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  907: wh-err= 0.941466  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  908: wh-err= 0.937772  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  909: wh-err= 0.927313  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  910: wh-err= 0.917904  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  911: wh-err= 0.920937  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  912: wh-err= 0.933194  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  913: wh-err= 0.935770  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  914: wh-err= 0.935078  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  915: wh-err= 0.932415  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  916: wh-err= 0.932496  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  917: wh-err= 0.935827  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  918: wh-err= 0.926637  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  919: wh-err= 0.931837  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  920: wh-err= 0.931298  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  921: wh-err= 0.933893  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  922: wh-err= 0.934483  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  923: wh-err= 0.935254  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  924: wh-err= 0.935695  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  925: wh-err= 0.936380  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  926: wh-err= 0.931696  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  927: wh-err= 0.941721  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  928: wh-err= 0.939776  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  929: wh-err= 0.941799  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  930: wh-err= 0.943337  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  931: wh-err= 0.936976  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  932: wh-err= 0.940701  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  933: wh-err= 0.943102  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  934: wh-err= 0.933098  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  935: wh-err= 0.934555  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  936: wh-err= 0.928003  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  937: wh-err= 0.925750  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  938: wh-err= 0.934433  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  939: wh-err= 0.933025  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  940: wh-err= 0.935050  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  941: wh-err= 0.932181  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  942: wh-err= 0.934466  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  943: wh-err= 0.924869  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  944: wh-err= 0.931388  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  945: wh-err= 0.933258  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  946: wh-err= 0.916966  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  947: wh-err= 0.919277  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  948: wh-err= 0.916459  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  949: wh-err= 0.921323  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  950: wh-err= 0.927240  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  951: wh-err= 0.927192  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  952: wh-err= 0.937402  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  953: wh-err= 0.942252  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  954: wh-err= 0.940286  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  955: wh-err= 0.934809  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  956: wh-err= 0.929609  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  957: wh-err= 0.933360  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  958: wh-err= 0.934965  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  959: wh-err= 0.932463  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  960: wh-err= 0.929227  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  961: wh-err= 0.936096  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  962: wh-err= 0.933819  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  963: wh-err= 0.925315  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  964: wh-err= 0.940690  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  965: wh-err= 0.945688  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  966: wh-err= 0.941277  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  967: wh-err= 0.939853  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  968: wh-err= 0.928578  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  969: wh-err= 0.933984  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  970: wh-err= 0.942366  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  971: wh-err= 0.933345  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  972: wh-err= 0.935332  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  973: wh-err= 0.931326  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  974: wh-err= 0.928939  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  975: wh-err= 0.928354  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  976: wh-err= 0.926973  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  977: wh-err= 0.923546  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  978: wh-err= 0.928798  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  979: wh-err= 0.936770  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  980: wh-err= 0.939196  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  981: wh-err= 0.934383  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  982: wh-err= 0.926717  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  983: wh-err= 0.927012  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  984: wh-err= 0.935121  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  985: wh-err= 0.927554  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  986: wh-err= 0.917326  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  987: wh-err= 0.925328  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  988: wh-err= 0.929990  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  989: wh-err= 0.934714  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  990: wh-err= 0.939694  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  991: wh-err= 0.935607  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  992: wh-err= 0.921865  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  993: wh-err= 0.935719  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  994: wh-err= 0.934412  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  995: wh-err= 0.934809  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  996: wh-err= 0.935131  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  997: wh-err= 0.938021  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  998: wh-err= 0.941892  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd  999: wh-err= 0.937003  th-err= 0.000000  test=      -nan  train= 0.0000000 
rnd 1000: wh-err= 0.930311  th-err= 0.000000  test=      -nan  train= 0.0000000 
=== END program1: ./run learn ../dataset2/train --- OK [3217s]

===== 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 [3s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 2800.000000 / 3260 = 0.858896
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [32s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [6s]

===== 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 [6s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
Copyright 2001 AT&T.  All rights reserved.



Test error = 6495.000000 / 7608 = 0.853707
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [74s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [14s]


real	55m52.315s
user	54m41.629s
sys	0m19.693s

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