 | Run 27849 |
| Creator | sidaw |
| Program | boostexter |
| Dataset | 20news |
| Task type | MulticlassClassification |
| Created | 253d16h ago |
| Download | Login required! |
Done! 
| 25m42s | |
| 95M | |
| MulticlassClassification | |
| 25m25s | |
| 0.060 | |
| 13s | |
| 0.242 | |
| 4s |
Log file
... 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0.0802636 rnd 829: wh-err= 0.998780 th-err= 0.054022 test= -nan train= 0.0800126 rnd 830: wh-err= 0.998740 th-err= 0.053954 test= -nan train= 0.0798243 rnd 831: wh-err= 0.998699 th-err= 0.053884 test= -nan train= 0.0798243 rnd 832: wh-err= 0.998798 th-err= 0.053819 test= -nan train= 0.0797615 rnd 833: wh-err= 0.998621 th-err= 0.053745 test= -nan train= 0.0795733 rnd 834: wh-err= 0.998770 th-err= 0.053679 test= -nan train= 0.0795733 rnd 835: wh-err= 0.998699 th-err= 0.053609 test= -nan train= 0.0795733 rnd 836: wh-err= 0.998672 th-err= 0.053538 test= -nan train= 0.0790085 rnd 837: wh-err= 0.998706 th-err= 0.053469 test= -nan train= 0.0788830 rnd 838: wh-err= 0.998730 th-err= 0.053401 test= -nan train= 0.0788830 rnd 839: wh-err= 0.998821 th-err= 0.053338 test= -nan train= 0.0788202 rnd 840: wh-err= 0.998790 th-err= 0.053273 test= -nan train= 0.0785064 rnd 841: wh-err= 0.998840 th-err= 0.053211 test= -nan train= 0.0783809 rnd 842: wh-err= 0.998740 th-err= 0.053144 test= -nan train= 0.0777534 rnd 843: wh-err= 0.998781 th-err= 0.053080 test= -nan train= 0.0777534 rnd 844: wh-err= 0.998634 th-err= 0.053007 test= -nan train= 0.0780671 rnd 845: wh-err= 0.998741 th-err= 0.052940 test= -nan train= 0.0777534 rnd 846: wh-err= 0.998703 th-err= 0.052872 test= -nan train= 0.0785064 rnd 847: wh-err= 0.998682 th-err= 0.052802 test= -nan train= 0.0783182 rnd 848: wh-err= 0.998690 th-err= 0.052733 test= -nan train= 0.0779416 rnd 849: wh-err= 0.998761 th-err= 0.052667 test= -nan train= 0.0778161 rnd 850: wh-err= 0.998718 th-err= 0.052600 test= -nan train= 0.0776279 rnd 851: wh-err= 0.998836 th-err= 0.052539 test= -nan train= 0.0775651 rnd 852: wh-err= 0.998787 th-err= 0.052475 test= -nan train= 0.0776279 rnd 853: wh-err= 0.998747 th-err= 0.052409 test= -nan train= 0.0774396 rnd 854: wh-err= 0.998796 th-err= 0.052346 test= -nan train= 0.0772513 rnd 855: wh-err= 0.998735 th-err= 0.052280 test= -nan train= 0.0771258 rnd 856: wh-err= 0.998816 th-err= 0.052218 test= -nan train= 0.0770003 rnd 857: wh-err= 0.998736 th-err= 0.052152 test= -nan train= 0.0768748 rnd 858: wh-err= 0.998807 th-err= 0.052090 test= -nan train= 0.0767493 rnd 859: wh-err= 0.998728 th-err= 0.052024 test= -nan train= 0.0765610 rnd 860: wh-err= 0.998782 th-err= 0.051960 test= -nan train= 0.0763728 rnd 861: wh-err= 0.998814 th-err= 0.051899 test= -nan train= 0.0758080 rnd 862: wh-err= 0.998825 th-err= 0.051838 test= -nan train= 0.0756825 rnd 863: wh-err= 0.998866 th-err= 0.051779 test= -nan train= 0.0757452 rnd 864: wh-err= 0.998765 th-err= 0.051715 test= -nan train= 0.0758080 rnd 865: wh-err= 0.998744 th-err= 0.051650 test= -nan train= 0.0756825 rnd 866: wh-err= 0.998703 th-err= 0.051583 test= -nan train= 0.0753687 rnd 867: wh-err= 0.998848 th-err= 0.051524 test= -nan train= 0.0753059 rnd 868: wh-err= 0.998806 th-err= 0.051462 test= -nan train= 0.0749922 rnd 869: wh-err= 0.998763 th-err= 0.051398 test= -nan train= 0.0749294 rnd 870: wh-err= 0.998847 th-err= 0.051339 test= -nan train= 0.0746784 rnd 871: wh-err= 0.998850 th-err= 0.051280 test= -nan train= 0.0744274 rnd 872: wh-err= 0.998866 th-err= 0.051222 test= -nan train= 0.0744274 rnd 873: wh-err= 0.998747 th-err= 0.051158 test= -nan train= 0.0745529 rnd 874: wh-err= 0.998774 th-err= 0.051095 test= -nan train= 0.0742391 rnd 875: wh-err= 0.998817 th-err= 0.051035 test= -nan train= 0.0741763 rnd 876: wh-err= 0.998752 th-err= 0.050971 test= -nan train= 0.0741763 rnd 877: wh-err= 0.998889 th-err= 0.050914 test= -nan train= 0.0739253 rnd 878: wh-err= 0.998739 th-err= 0.050850 test= -nan train= 0.0737371 rnd 879: wh-err= 0.998723 th-err= 0.050785 test= -nan train= 0.0742391 rnd 880: wh-err= 0.998672 th-err= 0.050718 test= -nan train= 0.0743019 rnd 881: wh-err= 0.998736 th-err= 0.050654 test= -nan train= 0.0739253 rnd 882: wh-err= 0.998751 th-err= 0.050590 test= -nan train= 0.0738626 rnd 883: wh-err= 0.998743 th-err= 0.050527 test= -nan train= 0.0736743 rnd 884: wh-err= 0.998879 th-err= 0.050470 test= -nan train= 0.0737371 rnd 885: wh-err= 0.998767 th-err= 0.050408 test= -nan train= 0.0736743 rnd 886: wh-err= 0.998810 th-err= 0.050348 test= -nan train= 0.0733605 rnd 887: wh-err= 0.998844 th-err= 0.050290 test= -nan train= 0.0732978 rnd 888: wh-err= 0.998820 th-err= 0.050230 test= -nan train= 0.0731723 rnd 889: wh-err= 0.998817 th-err= 0.050171 test= -nan train= 0.0729212 rnd 890: wh-err= 0.998817 th-err= 0.050112 test= -nan train= 0.0730468 rnd 891: wh-err= 0.998711 th-err= 0.050047 test= -nan train= 0.0724820 rnd 892: wh-err= 0.998789 th-err= 0.049986 test= -nan train= 0.0724820 rnd 893: wh-err= 0.998751 th-err= 0.049924 test= -nan train= 0.0723564 rnd 894: wh-err= 0.998706 th-err= 0.049859 test= -nan train= 0.0720427 rnd 895: wh-err= 0.998719 th-err= 0.049795 test= -nan train= 0.0721054 rnd 896: wh-err= 0.998815 th-err= 0.049736 test= -nan train= 0.0719172 rnd 897: wh-err= 0.998893 th-err= 0.049681 test= -nan train= 0.0718544 rnd 898: wh-err= 0.998827 th-err= 0.049623 test= -nan train= 0.0716661 rnd 899: wh-err= 0.998814 th-err= 0.049564 test= -nan train= 0.0715406 rnd 900: wh-err= 0.998767 th-err= 0.049503 test= -nan train= 0.0711641 rnd 901: wh-err= 0.998788 th-err= 0.049443 test= -nan train= 0.0712269 rnd 902: wh-err= 0.998735 th-err= 0.049381 test= -nan train= 0.0708503 rnd 903: wh-err= 0.998851 th-err= 0.049324 test= -nan train= 0.0707248 rnd 904: wh-err= 0.998745 th-err= 0.049262 test= -nan train= 0.0708503 rnd 905: wh-err= 0.998812 th-err= 0.049203 test= -nan train= 0.0707876 rnd 906: wh-err= 0.998864 th-err= 0.049148 test= -nan train= 0.0705993 rnd 907: wh-err= 0.998773 th-err= 0.049087 test= -nan train= 0.0702228 rnd 908: wh-err= 0.998825 th-err= 0.049030 test= -nan train= 0.0702228 rnd 909: wh-err= 0.998817 th-err= 0.048972 test= -nan train= 0.0699090 rnd 910: wh-err= 0.998751 th-err= 0.048910 test= -nan train= 0.0699718 rnd 911: wh-err= 0.998761 th-err= 0.048850 test= -nan train= 0.0699718 rnd 912: wh-err= 0.998732 th-err= 0.048788 test= -nan train= 0.0699718 rnd 913: wh-err= 0.998847 th-err= 0.048732 test= -nan train= 0.0700345 rnd 914: wh-err= 0.998810 th-err= 0.048674 test= -nan train= 0.0700345 rnd 915: wh-err= 0.998795 th-err= 0.048615 test= -nan train= 0.0698463 rnd 916: wh-err= 0.998826 th-err= 0.048558 test= -nan train= 0.0697207 rnd 917: wh-err= 0.998753 th-err= 0.048497 test= -nan train= 0.0693442 rnd 918: wh-err= 0.998698 th-err= 0.048434 test= -nan train= 0.0694697 rnd 919: wh-err= 0.998816 th-err= 0.048377 test= -nan train= 0.0691559 rnd 920: wh-err= 0.998868 th-err= 0.048322 test= -nan train= 0.0691559 rnd 921: wh-err= 0.998809 th-err= 0.048265 test= -nan train= 0.0690932 rnd 922: wh-err= 0.998772 th-err= 0.048205 test= -nan train= 0.0690304 rnd 923: wh-err= 0.998804 th-err= 0.048148 test= -nan train= 0.0687794 rnd 924: wh-err= 0.998846 th-err= 0.048092 test= -nan train= 0.0687167 rnd 925: wh-err= 0.998835 th-err= 0.048036 test= -nan train= 0.0687794 rnd 926: wh-err= 0.998785 th-err= 0.047978 test= -nan train= 0.0686539 rnd 927: wh-err= 0.998792 th-err= 0.047920 test= -nan train= 0.0685284 rnd 928: wh-err= 0.998878 th-err= 0.047866 test= -nan train= 0.0683401 rnd 929: wh-err= 0.998839 th-err= 0.047810 test= -nan train= 0.0680891 rnd 930: wh-err= 0.998775 th-err= 0.047752 test= -nan train= 0.0680891 rnd 931: wh-err= 0.998798 th-err= 0.047694 test= -nan train= 0.0679636 rnd 932: wh-err= 0.998747 th-err= 0.047635 test= -nan train= 0.0680264 rnd 933: wh-err= 0.998800 th-err= 0.047577 test= -nan train= 0.0676498 rnd 934: wh-err= 0.998752 th-err= 0.047518 test= -nan train= 0.0673988 rnd 935: wh-err= 0.998752 th-err= 0.047459 test= -nan train= 0.0667713 rnd 936: wh-err= 0.998784 th-err= 0.047401 test= -nan train= 0.0668968 rnd 937: wh-err= 0.998784 th-err= 0.047343 test= -nan train= 0.0666457 rnd 938: wh-err= 0.998823 th-err= 0.047288 test= -nan train= 0.0665830 rnd 939: wh-err= 0.998858 th-err= 0.047234 test= -nan train= 0.0665202 rnd 940: wh-err= 0.998780 th-err= 0.047176 test= -nan train= 0.0663947 rnd 941: wh-err= 0.998904 th-err= 0.047124 test= -nan train= 0.0662692 rnd 942: wh-err= 0.998901 th-err= 0.047073 test= -nan train= 0.0661437 rnd 943: wh-err= 0.998816 th-err= 0.047017 test= -nan train= 0.0658927 rnd 944: wh-err= 0.998851 th-err= 0.046963 test= -nan train= 0.0660182 rnd 945: wh-err= 0.998899 th-err= 0.046911 test= -nan train= 0.0659554 rnd 946: wh-err= 0.998836 th-err= 0.046857 test= -nan train= 0.0658299 rnd 947: wh-err= 0.998779 th-err= 0.046799 test= -nan train= 0.0660182 rnd 948: wh-err= 0.998882 th-err= 0.046747 test= -nan train= 0.0658927 rnd 949: wh-err= 0.998864 th-err= 0.046694 test= -nan train= 0.0657044 rnd 950: wh-err= 0.998766 th-err= 0.046636 test= -nan train= 0.0657044 rnd 951: wh-err= 0.998791 th-err= 0.046580 test= -nan train= 0.0655789 rnd 952: wh-err= 0.998803 th-err= 0.046524 test= -nan train= 0.0653279 rnd 953: wh-err= 0.998777 th-err= 0.046467 test= -nan train= 0.0652024 rnd 954: wh-err= 0.998766 th-err= 0.046410 test= -nan train= 0.0650141 rnd 955: wh-err= 0.998788 th-err= 0.046354 test= -nan train= 0.0647631 rnd 956: wh-err= 0.998775 th-err= 0.046297 test= -nan train= 0.0644493 rnd 957: wh-err= 0.998831 th-err= 0.046243 test= -nan train= 0.0642611 rnd 958: wh-err= 0.998850 th-err= 0.046190 test= -nan train= 0.0641983 rnd 959: wh-err= 0.998813 th-err= 0.046135 test= -nan train= 0.0643238 rnd 960: wh-err= 0.998869 th-err= 0.046083 test= -nan train= 0.0642611 rnd 961: wh-err= 0.998805 th-err= 0.046028 test= -nan train= 0.0641983 rnd 962: wh-err= 0.998794 th-err= 0.045972 test= -nan train= 0.0640100 rnd 963: wh-err= 0.998891 th-err= 0.045921 test= -nan train= 0.0640100 rnd 964: wh-err= 0.998770 th-err= 0.045865 test= -nan train= 0.0640728 rnd 965: wh-err= 0.998805 th-err= 0.045810 test= -nan train= 0.0637590 rnd 966: wh-err= 0.998834 th-err= 0.045756 test= -nan train= 0.0636335 rnd 967: wh-err= 0.998924 th-err= 0.045707 test= -nan train= 0.0635080 rnd 968: wh-err= 0.998859 th-err= 0.045655 test= -nan train= 0.0633825 rnd 969: wh-err= 0.998794 th-err= 0.045600 test= -nan train= 0.0632570 rnd 970: wh-err= 0.998844 th-err= 0.045547 test= -nan train= 0.0634452 rnd 971: wh-err= 0.998810 th-err= 0.045493 test= -nan train= 0.0633825 rnd 972: wh-err= 0.998820 th-err= 0.045439 test= -nan train= 0.0631942 rnd 973: wh-err= 0.998791 th-err= 0.045384 test= -nan train= 0.0629432 rnd 974: wh-err= 0.998837 th-err= 0.045332 test= -nan train= 0.0629432 rnd 975: wh-err= 0.998843 th-err= 0.045279 test= -nan train= 0.0628177 rnd 976: wh-err= 0.998805 th-err= 0.045225 test= -nan train= 0.0626294 rnd 977: wh-err= 0.998873 th-err= 0.045174 test= -nan train= 0.0627549 rnd 978: wh-err= 0.998803 th-err= 0.045120 test= -nan train= 0.0622529 rnd 979: wh-err= 0.998834 th-err= 0.045067 test= -nan train= 0.0621274 rnd 980: wh-err= 0.998881 th-err= 0.045017 test= -nan train= 0.0621901 rnd 981: wh-err= 0.998827 th-err= 0.044964 test= -nan train= 0.0620646 rnd 982: wh-err= 0.998840 th-err= 0.044912 test= -nan train= 0.0618136 rnd 983: wh-err= 0.998880 th-err= 0.044862 test= -nan train= 0.0616881 rnd 984: wh-err= 0.998904 th-err= 0.044813 test= -nan train= 0.0616254 rnd 985: wh-err= 0.998904 th-err= 0.044763 test= -nan train= 0.0615626 rnd 986: wh-err= 0.998908 th-err= 0.044715 test= -nan train= 0.0613743 rnd 987: wh-err= 0.998770 th-err= 0.044660 test= -nan train= 0.0613116 rnd 988: wh-err= 0.998833 th-err= 0.044607 test= -nan train= 0.0613116 rnd 989: wh-err= 0.998797 th-err= 0.044554 test= -nan train= 0.0613743 rnd 990: wh-err= 0.998764 th-err= 0.044499 test= -nan train= 0.0609978 rnd 991: wh-err= 0.998897 th-err= 0.044450 test= -nan train= 0.0608723 rnd 992: wh-err= 0.998861 th-err= 0.044399 test= -nan train= 0.0609350 rnd 993: wh-err= 0.998807 th-err= 0.044346 test= -nan train= 0.0608723 rnd 994: wh-err= 0.998859 th-err= 0.044295 test= -nan train= 0.0608723 rnd 995: wh-err= 0.998779 th-err= 0.044241 test= -nan train= 0.0609350 rnd 996: wh-err= 0.998867 th-err= 0.044191 test= -nan train= 0.0606840 rnd 997: wh-err= 0.998816 th-err= 0.044139 test= -nan train= 0.0606213 rnd 998: wh-err= 0.998834 th-err= 0.044087 test= -nan train= 0.0604330 rnd 999: wh-err= 0.998833 th-err= 0.044036 test= -nan train= 0.0604330 rnd 1000: wh-err= 0.998768 th-err= 0.043982 test= -nan train= 0.0599937 === END program1: ./run learn ../dataset2/train --- OK [1525s] ===== 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 = 15935.000000 / 15935 = 1.000000 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [13s] === 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 [0s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out Copyright 2001 AT&T. All rights reserved. Test error = 3993.000000 / 3993 = 1.000000 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [4s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s] real 25m46.015s user 25m19.827s sys 0m4.116s
Run specification 
Results
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