 | Run 19887 |
| Creator | internal |
| Program | minimalist-boost |
| Dataset | Brunato_Battiti_2 |
| Task type | MulticlassClassification |
| Created | 319d11h ago |
Done! 
| BinaryClassification | |
| 1s | |
| 0 | |
| 0s | |
| 0.065 | |
| 0s |
Log file
... (lines omitted) ... iteration:627 feature:3 threshold:30.5 min-objective:0.952106 iteration:628 feature:3 threshold:33.5 min-objective:0.935256 iteration:629 feature:5 threshold:59.5 min-objective:0.944567 iteration:630 feature:6 threshold:16.5 min-objective:0.956273 iteration:631 feature:6 threshold:21.5 min-objective:0.925033 iteration:632 feature:5 threshold:46.5 min-objective:0.932413 iteration:633 feature:5 threshold:34.5 min-objective:0.944269 iteration:634 feature:1 threshold:31.5 min-objective:0.950877 iteration:635 feature:4 threshold:40.5 min-objective:0.96228 iteration:636 feature:6 threshold:23.5 min-objective:0.960551 iteration:637 feature:1 threshold:8.5 min-objective:0.96477 iteration:638 feature:2 threshold:33.5 min-objective:0.951316 iteration:639 feature:2 threshold:38.5 min-objective:0.927138 iteration:640 feature:5 threshold:59.5 min-objective:0.953228 iteration:641 feature:5 threshold:52 min-objective:0.948176 iteration:642 feature:4 threshold:23.5 min-objective:0.939187 iteration:643 feature:1 threshold:22.5 min-objective:0.934584 iteration:644 feature:1 threshold:30.5 min-objective:0.934266 iteration:645 feature:6 threshold:14.5 min-objective:0.945422 iteration:646 feature:4 threshold:21.5 min-objective:0.955753 iteration:647 feature:3 threshold:33.5 min-objective:0.954286 iteration:648 feature:3 threshold:30.5 min-objective:0.937618 iteration:649 feature:1 threshold:32.5 min-objective:0.944783 iteration:650 feature:1 threshold:22.5 min-objective:0.964103 iteration:651 feature:5 threshold:37.5 min-objective:0.945503 iteration:652 feature:4 threshold:19.5 min-objective:0.943845 iteration:653 feature:3 threshold:20.5 min-objective:0.942776 iteration:654 feature:2 threshold:33.5 min-objective:0.943202 iteration:655 feature:1 threshold:13.5 min-objective:0.936296 iteration:656 feature:5 threshold:37.5 min-objective:0.939484 iteration:657 feature:4 threshold:38.5 min-objective:0.920268 iteration:658 feature:6 threshold:23.5 min-objective:0.951608 iteration:659 feature:3 threshold:33.5 min-objective:0.959524 iteration:660 feature:3 threshold:17 min-objective:0.958109 iteration:661 feature:6 threshold:16.5 min-objective:0.924722 iteration:662 feature:2 threshold:33.5 min-objective:0.943401 iteration:663 feature:4 threshold:21.5 min-objective:0.942627 iteration:664 feature:4 threshold:38.5 min-objective:0.937088 iteration:665 feature:5 threshold:52 min-objective:0.929078 iteration:666 feature:5 threshold:59.5 min-objective:0.933504 iteration:667 feature:2 threshold:38.5 min-objective:0.93936 iteration:668 feature:1 threshold:31.5 min-objective:0.961445 iteration:669 feature:1 threshold:30.5 min-objective:0.955296 iteration:670 feature:6 threshold:18.5 min-objective:0.958987 iteration:671 feature:6 threshold:21.5 min-objective:0.948373 iteration:672 feature:3 threshold:37.5 min-objective:0.951415 iteration:673 feature:1 threshold:32.5 min-objective:0.957437 iteration:674 feature:4 threshold:38.5 min-objective:0.962029 iteration:675 feature:2 threshold:31.5 min-objective:0.965561 iteration:676 feature:1 threshold:18.5 min-objective:0.956244 iteration:677 feature:2 threshold:33.5 min-objective:0.952313 iteration:678 feature:2 threshold:38.5 min-objective:0.942313 iteration:679 feature:4 threshold:21.5 min-objective:0.944039 iteration:680 feature:3 threshold:33.5 min-objective:0.93971 iteration:681 feature:1 threshold:26.5 min-objective:0.903325 iteration:682 feature:3 threshold:30.5 min-objective:0.941268 iteration:683 feature:5 threshold:37.5 min-objective:0.936577 iteration:684 feature:6 threshold:23.5 min-objective:0.936256 iteration:685 feature:5 threshold:52 min-objective:0.957729 iteration:686 feature:5 threshold:59.5 min-objective:0.944225 iteration:687 feature:6 threshold:14.5 min-objective:0.948395 iteration:688 feature:6 threshold:10.5 min-objective:0.94807 iteration:689 feature:1 threshold:29.5 min-objective:0.941919 iteration:690 feature:4 threshold:40.5 min-objective:0.930145 iteration:691 feature:6 threshold:16.5 min-objective:0.958934 iteration:692 feature:3 threshold:17 min-objective:0.947292 iteration:693 feature:3 threshold:33.5 min-objective:0.936014 iteration:694 feature:2 threshold:33.5 min-objective:0.936019 iteration:695 feature:1 threshold:20.5 min-objective:0.944913 iteration:696 feature:4 threshold:21.5 min-objective:0.935471 iteration:697 feature:1 threshold:32.5 min-objective:0.93351 iteration:698 feature:4 threshold:38.5 min-objective:0.948874 iteration:699 feature:2 threshold:52.5 min-objective:0.947496 iteration:700 feature:2 threshold:33.5 min-objective:0.961509 iteration:701 feature:2 threshold:38.5 min-objective:0.943256 iteration:702 feature:2 threshold:41.5 min-objective:0.940046 iteration:703 feature:3 threshold:33.5 min-objective:0.938631 iteration:704 feature:5 threshold:29.5 min-objective:0.954408 iteration:705 feature:5 threshold:26.5 min-objective:0.957372 iteration:706 feature:4 threshold:20.5 min-objective:0.961949 iteration:707 feature:5 threshold:34.5 min-objective:0.946103 iteration:708 feature:3 threshold:20.5 min-objective:0.929073 iteration:709 feature:6 threshold:23.5 min-objective:0.947964 iteration:710 feature:4 threshold:38.5 min-objective:0.953316 iteration:711 feature:6 threshold:16.5 min-objective:0.946112 iteration:712 feature:5 threshold:37.5 min-objective:0.950502 iteration:713 feature:4 threshold:33.5 min-objective:0.937631 iteration:714 feature:4 threshold:37.5 min-objective:0.946996 iteration:715 feature:5 threshold:59.5 min-objective:0.946112 iteration:716 feature:4 threshold:38.5 min-objective:0.956265 iteration:717 feature:5 threshold:52 min-objective:0.960689 iteration:718 feature:3 threshold:22.5 min-objective:0.939011 iteration:719 feature:1 threshold:22.5 min-objective:0.95776 iteration:720 feature:4 threshold:23.5 min-objective:0.94068 iteration:721 feature:6 threshold:14.5 min-objective:0.958328 iteration:722 feature:3 threshold:17 min-objective:0.926277 iteration:723 feature:2 threshold:33.5 min-objective:0.956021 iteration:724 feature:1 threshold:13.5 min-objective:0.940482 iteration:725 feature:3 threshold:33.5 min-objective:0.949107 iteration:726 feature:3 threshold:29.5 min-objective:0.94957 iteration:727 feature:1 threshold:28.5 min-objective:0.943308 iteration:728 feature:1 threshold:31.5 min-objective:0.918246 iteration:729 feature:1 threshold:26.5 min-objective:0.959359 iteration:730 feature:5 threshold:37.5 min-objective:0.935738 iteration:731 feature:5 threshold:52 min-objective:0.955094 iteration:732 feature:5 threshold:59.5 min-objective:0.955228 iteration:733 feature:6 threshold:14.5 min-objective:0.950158 iteration:734 feature:5 threshold:27.5 min-objective:0.956422 iteration:735 feature:2 threshold:31.5 min-objective:0.948472 iteration:736 feature:3 threshold:20.5 min-objective:0.958026 iteration:737 feature:1 threshold:28.5 min-objective:0.941248 iteration:738 feature:4 threshold:40.5 min-objective:0.928245 iteration:739 feature:6 threshold:23.5 min-objective:0.952569 iteration:740 feature:1 threshold:20.5 min-objective:0.96018 iteration:741 feature:2 threshold:33.5 min-objective:0.941738 iteration:742 feature:2 threshold:38.5 min-objective:0.940415 iteration:743 feature:6 threshold:21.5 min-objective:0.946359 iteration:744 feature:1 threshold:32.5 min-objective:0.938977 iteration:745 feature:5 threshold:27.5 min-objective:0.958974 iteration:746 feature:5 threshold:26.5 min-objective:0.938124 iteration:747 feature:5 threshold:59.5 min-objective:0.955552 iteration:748 feature:5 threshold:52 min-objective:0.962852 iteration:749 feature:6 threshold:14.5 min-objective:0.94765 iteration:750 feature:4 threshold:22.5 min-objective:0.930078 iteration:751 feature:6 threshold:10.5 min-objective:0.945785 iteration:752 feature:4 threshold:40.5 min-objective:0.947704 iteration:753 feature:3 threshold:33.5 min-objective:0.94762 iteration:754 feature:6 threshold:16.5 min-objective:0.937464 iteration:755 feature:5 threshold:37.5 min-objective:0.946422 iteration:756 feature:1 threshold:26.5 min-objective:0.930499 iteration:757 feature:1 threshold:29.5 min-objective:0.942187 iteration:758 feature:3 threshold:17 min-objective:0.933371 iteration:759 feature:4 threshold:40.5 min-objective:0.944157 iteration:760 feature:6 threshold:23.5 min-objective:0.952452 iteration:761 feature:1 threshold:13.5 min-objective:0.954931 iteration:762 feature:2 threshold:33.5 min-objective:0.91804 iteration:763 feature:5 threshold:40 min-objective:0.947219 iteration:764 feature:4 threshold:20.5 min-objective:0.932657 iteration:765 feature:3 threshold:17 min-objective:0.945942 iteration:766 feature:4 threshold:21.5 min-objective:0.941299 iteration:767 feature:1 threshold:22.5 min-objective:0.934785 iteration:768 feature:5 threshold:34.5 min-objective:0.949667 iteration:769 feature:1 threshold:32.5 min-objective:0.940887 iteration:770 feature:3 threshold:33.5 min-objective:0.94607 iteration:771 feature:5 threshold:29.5 min-objective:0.948845 iteration:772 feature:2 threshold:33.5 min-objective:0.949155 iteration:773 feature:4 threshold:40.5 min-objective:0.946134 iteration:774 feature:2 threshold:38.5 min-objective:0.918831 iteration:775 feature:2 threshold:41.5 min-objective:0.952484 iteration:776 feature:2 threshold:52.5 min-objective:0.94065 iteration:777 feature:5 threshold:26.5 min-objective:0.959015 iteration:778 feature:1 threshold:20.5 min-objective:0.958909 iteration:779 feature:2 threshold:36.5 min-objective:0.953072 iteration:780 feature:3 threshold:33.5 min-objective:0.965148 iteration:781 feature:4 threshold:21.5 min-objective:0.955038 iteration:782 feature:4 threshold:33.5 min-objective:0.923771 iteration:783 feature:2 threshold:38.5 min-objective:0.918923 iteration:784 feature:1 threshold:32.5 min-objective:0.940351 iteration:785 feature:5 threshold:59.5 min-objective:0.954092 iteration:786 feature:1 threshold:28.5 min-objective:0.949679 iteration:787 feature:4 threshold:33.5 min-objective:0.942194 iteration:788 feature:4 threshold:21.5 min-objective:0.954802 iteration:789 feature:4 threshold:19.5 min-objective:0.941516 iteration:790 feature:2 threshold:31.5 min-objective:0.951343 iteration:791 feature:3 threshold:37.5 min-objective:0.957923 iteration:792 feature:5 threshold:27.5 min-objective:0.962033 iteration:793 feature:5 threshold:34.5 min-objective:0.940529 iteration:794 feature:1 threshold:26.5 min-objective:0.937694 iteration:795 feature:5 threshold:26.5 min-objective:0.961757 iteration:796 feature:2 threshold:38.5 min-objective:0.957312 iteration:797 feature:2 threshold:36.5 min-objective:0.949228 iteration:798 feature:1 threshold:18.5 min-objective:0.950177 iteration:799 feature:5 threshold:40 min-objective:0.950281 iteration:800 feature:5 threshold:52 min-objective:0.922032 iteration:801 feature:5 threshold:59.5 min-objective:0.945997 iteration:802 feature:6 threshold:23.5 min-objective:0.95491 iteration:803 feature:4 threshold:38.5 min-objective:0.952397 iteration:804 feature:3 threshold:33.5 min-objective:0.958052 iteration:805 feature:6 threshold:16.5 min-objective:0.950906 iteration:806 feature:6 threshold:21.5 min-objective:0.934137 iteration:807 feature:5 threshold:52 min-objective:0.950257 iteration:808 feature:1 threshold:29.5 min-objective:0.943258 iteration:809 feature:5 threshold:59.5 min-objective:0.931877 iteration:810 feature:5 threshold:44.5 min-objective:0.947986 iteration:811 feature:4 threshold:38.5 min-objective:0.949392 iteration:812 feature:4 threshold:21.5 min-objective:0.951065 iteration:813 feature:6 threshold:16.5 min-objective:0.94059 iteration:814 feature:3 threshold:20.5 min-objective:0.949899 iteration:815 feature:6 threshold:14.5 min-objective:0.948185 iteration:816 feature:5 threshold:37.5 min-objective:0.944041 iteration:817 feature:6 threshold:10.5 min-objective:0.945877 iteration:818 feature:2 threshold:33.5 min-objective:0.932462 iteration:819 feature:1 threshold:31.5 min-objective:0.929841 iteration:820 feature:4 threshold:40.5 min-objective:0.936188 iteration:821 feature:3 threshold:33.5 min-objective:0.941357 iteration:822 feature:1 threshold:20.5 min-objective:0.954267 iteration:823 feature:3 threshold:29.5 min-objective:0.944741 iteration:824 feature:1 threshold:29.5 min-objective:0.938112 iteration:825 feature:5 threshold:59.5 min-objective:0.945233 iteration:826 feature:5 threshold:52 min-objective:0.933724 iteration:827 feature:6 threshold:23.5 min-objective:0.947854 iteration:828 feature:6 threshold:14.5 min-objective:0.957672 iteration:829 feature:4 threshold:22.5 min-objective:0.940272 iteration:830 feature:1 threshold:22.5 min-objective:0.928743 iteration:831 feature:5 threshold:40 min-objective:0.95009 iteration:832 feature:3 threshold:20.5 min-objective:0.950233 iteration:833 feature:2 threshold:33.5 min-objective:0.94686 iteration:834 feature:1 threshold:13.5 min-objective:0.934767 iteration:835 feature:4 threshold:38.5 min-objective:0.946183 iteration:836 feature:1 threshold:32.5 min-objective:0.961817 iteration:837 feature:1 threshold:30.5 min-objective:0.960897 iteration:838 feature:6 threshold:16.5 min-objective:0.948184 iteration:839 feature:3 threshold:20.5 min-objective:0.943469 iteration:840 feature:5 threshold:40 min-objective:0.935651 iteration:841 feature:6 threshold:18.5 min-objective:0.94901 iteration:842 feature:4 threshold:38.5 min-objective:0.950235 iteration:843 feature:3 threshold:33.5 min-objective:0.955013 iteration:844 feature:3 threshold:30.5 min-objective:0.934739 iteration:845 feature:3 threshold:27.5 min-objective:0.956078 iteration:846 feature:2 threshold:31.5 min-objective:0.953043 iteration:847 feature:4 threshold:20.5 min-objective:0.933349 iteration:848 feature:6 threshold:10.5 min-objective:0.954493 iteration:849 feature:4 threshold:21.5 min-objective:0.953703 iteration:850 feature:1 threshold:26.5 min-objective:0.928719 iteration:851 feature:1 threshold:29.5 min-objective:0.94383 iteration:852 feature:1 threshold:31.5 min-objective:0.937269 iteration:853 feature:3 threshold:33.5 min-objective:0.962135 iteration:854 feature:2 threshold:38.5 min-objective:0.956921 iteration:855 feature:2 threshold:33.5 min-objective:0.94027 iteration:856 feature:4 threshold:40.5 min-objective:0.934125 iteration:857 feature:6 threshold:23.5 min-objective:0.960967 iteration:858 feature:6 threshold:20.5 min-objective:0.942686 iteration:859 feature:6 threshold:16.5 min-objective:0.942556 iteration:860 feature:3 threshold:17 min-objective:0.929247 iteration:861 feature:5 threshold:59.5 min-objective:0.946469 iteration:862 feature:1 threshold:13.5 min-objective:0.952747 iteration:863 feature:2 threshold:31.5 min-objective:0.957721 iteration:864 feature:1 threshold:32.5 min-objective:0.956103 iteration:865 feature:5 threshold:37.5 min-objective:0.948577 iteration:866 feature:5 threshold:27.5 min-objective:0.935154 iteration:867 feature:2 threshold:38.5 min-objective:0.94596 iteration:868 feature:4 threshold:40.5 min-objective:0.932792 iteration:869 feature:2 threshold:33.5 min-objective:0.939155 iteration:870 feature:3 threshold:37.5 min-objective:0.949906 iteration:871 feature:5 threshold:52 min-objective:0.945355 iteration:872 feature:6 threshold:14.5 min-objective:0.943109 iteration:873 feature:5 threshold:34.5 min-objective:0.931288 iteration:874 feature:3 threshold:17 min-objective:0.917937 iteration:875 feature:6 threshold:23.5 min-objective:0.927595 iteration:876 feature:5 threshold:59.5 min-objective:0.959032 iteration:877 feature:6 threshold:14.5 min-objective:0.956741 iteration:878 feature:3 threshold:30.5 min-objective:0.947141 iteration:879 feature:3 threshold:33.5 min-objective:0.948347 iteration:880 feature:6 threshold:20.5 min-objective:0.949194 iteration:881 feature:1 threshold:32.5 min-objective:0.948223 iteration:882 feature:2 threshold:38.5 min-objective:0.954877 iteration:883 feature:4 threshold:38.5 min-objective:0.946026 iteration:884 feature:4 threshold:21.5 min-objective:0.947034 iteration:885 feature:1 threshold:22.5 min-objective:0.918616 iteration:886 feature:2 threshold:33.5 min-objective:0.936631 iteration:887 feature:4 threshold:21.5 min-objective:0.950516 iteration:888 feature:5 threshold:52 min-objective:0.937154 iteration:889 feature:1 threshold:20.5 min-objective:0.948973 iteration:890 feature:2 threshold:52.5 min-objective:0.941771 iteration:891 feature:5 threshold:59.5 min-objective:0.943018 iteration:892 feature:6 threshold:23.5 min-objective:0.945626 iteration:893 feature:3 threshold:33.5 min-objective:0.941197 iteration:894 feature:4 threshold:21.5 min-objective:0.94745 iteration:895 feature:2 threshold:33.5 min-objective:0.939826 iteration:896 feature:5 threshold:52 min-objective:0.932113 iteration:897 feature:6 threshold:14.5 min-objective:0.920314 iteration:898 feature:4 threshold:38.5 min-objective:0.943681 iteration:899 feature:5 threshold:37.5 min-objective:0.932716 iteration:900 feature:3 threshold:20.5 min-objective:0.923241 iteration:901 feature:6 threshold:16.5 min-objective:0.939005 iteration:902 feature:6 threshold:10.5 min-objective:0.955724 iteration:903 feature:4 threshold:38.5 min-objective:0.951976 iteration:904 feature:1 threshold:29.5 min-objective:0.941338 iteration:905 feature:5 threshold:59.5 min-objective:0.945766 iteration:906 feature:1 threshold:20.5 min-objective:0.937569 iteration:907 feature:6 threshold:23.5 min-objective:0.949757 iteration:908 feature:2 threshold:33.5 min-objective:0.944531 iteration:909 feature:5 threshold:52 min-objective:0.951562 iteration:910 feature:5 threshold:37.5 min-objective:0.944519 iteration:911 feature:5 threshold:29.5 min-objective:0.926869 iteration:912 feature:6 threshold:14.5 min-objective:0.924731 iteration:913 feature:6 threshold:10.5 min-objective:0.950337 iteration:914 feature:3 threshold:33.5 min-objective:0.94951 iteration:915 feature:4 threshold:40.5 min-objective:0.949689 iteration:916 feature:5 threshold:34.5 min-objective:0.951747 iteration:917 feature:1 threshold:32.5 min-objective:0.942019 iteration:918 feature:3 threshold:29.5 min-objective:0.948198 iteration:919 feature:2 threshold:33.5 min-objective:0.938138 iteration:920 feature:1 threshold:18.5 min-objective:0.940568 iteration:921 feature:4 threshold:17.5 min-objective:0.933371 iteration:922 feature:5 threshold:59.5 min-objective:0.950725 iteration:923 feature:5 threshold:52 min-objective:0.948037 iteration:924 feature:6 threshold:23.5 min-objective:0.951842 iteration:925 feature:5 threshold:40 min-objective:0.949486 iteration:926 feature:4 threshold:19.5 min-objective:0.925615 iteration:927 feature:4 threshold:21.5 min-objective:0.939565 iteration:928 feature:1 threshold:22.5 min-objective:0.923743 iteration:929 feature:3 threshold:33.5 min-objective:0.961057 iteration:930 feature:4 threshold:21.5 min-objective:0.954017 iteration:931 feature:2 threshold:33.5 min-objective:0.942577 iteration:932 feature:4 threshold:40.5 min-objective:0.937015 iteration:933 feature:2 threshold:38.5 min-objective:0.923267 iteration:934 feature:4 threshold:33.5 min-objective:0.935637 iteration:935 feature:5 threshold:37.5 min-objective:0.941276 iteration:936 feature:5 threshold:29.5 min-objective:0.931546 iteration:937 feature:1 threshold:31.5 min-objective:0.949871 iteration:938 feature:2 threshold:33.5 min-objective:0.943799 iteration:939 feature:2 threshold:38.5 min-objective:0.944497 iteration:940 feature:3 threshold:37.5 min-objective:0.94528 iteration:941 feature:5 threshold:59.5 min-objective:0.950618 iteration:942 feature:4 threshold:40.5 min-objective:0.951484 iteration:943 feature:5 threshold:52 min-objective:0.95569 iteration:944 feature:5 threshold:34.5 min-objective:0.94052 iteration:945 feature:6 threshold:16.5 min-objective:0.940057 iteration:946 feature:5 threshold:26.5 min-objective:0.952547 iteration:947 feature:4 threshold:33.5 min-objective:0.949063 iteration:948 feature:5 threshold:37.5 min-objective:0.942996 iteration:949 feature:6 threshold:23.5 min-objective:0.94098 iteration:950 feature:3 threshold:17 min-objective:0.953073 iteration:951 feature:6 threshold:14.5 min-objective:0.940274 iteration:952 feature:5 threshold:27.5 min-objective:0.947335 iteration:953 feature:6 threshold:21.5 min-objective:0.942332 iteration:954 feature:5 threshold:59.5 min-objective:0.946912 iteration:955 feature:4 threshold:37.5 min-objective:0.947063 iteration:956 feature:4 threshold:40.5 min-objective:0.929742 iteration:957 feature:6 threshold:23.5 min-objective:0.94802 iteration:958 feature:3 threshold:33.5 min-objective:0.955485 iteration:959 feature:5 threshold:52 min-objective:0.953338 iteration:960 feature:6 threshold:14.5 min-objective:0.950014 iteration:961 feature:2 threshold:33.5 min-objective:0.936818 iteration:962 feature:4 threshold:21.5 min-objective:0.941809 iteration:963 feature:2 threshold:52.5 min-objective:0.937176 iteration:964 feature:6 threshold:10.5 min-objective:0.934015 iteration:965 feature:1 threshold:20.5 min-objective:0.9246 iteration:966 feature:2 threshold:33.5 min-objective:0.95183 iteration:967 feature:4 threshold:38.5 min-objective:0.954456 iteration:968 feature:1 threshold:31.5 min-objective:0.957458 iteration:969 feature:5 threshold:37.5 min-objective:0.956592 iteration:970 feature:3 threshold:20.5 min-objective:0.946201 iteration:971 feature:6 threshold:14.5 min-objective:0.921002 iteration:972 feature:5 threshold:27.5 min-objective:0.950222 iteration:973 feature:5 threshold:26.5 min-objective:0.950583 iteration:974 feature:6 threshold:23.5 min-objective:0.950387 iteration:975 feature:5 threshold:59.5 min-objective:0.952495 iteration:976 feature:5 threshold:50.5 min-objective:0.942208 iteration:977 feature:5 threshold:37.5 min-objective:0.923033 iteration:978 feature:1 threshold:13.5 min-objective:0.940826 iteration:979 feature:2 threshold:33.5 min-objective:0.944988 iteration:980 feature:5 threshold:27.5 min-objective:0.947815 iteration:981 feature:3 threshold:33.5 min-objective:0.950875 iteration:982 feature:2 threshold:38.5 min-objective:0.940384 iteration:983 feature:4 threshold:40.5 min-objective:0.919127 iteration:984 feature:3 threshold:30.5 min-objective:0.956124 iteration:985 feature:5 threshold:59.5 min-objective:0.94751 iteration:986 feature:1 threshold:29.5 min-objective:0.954225 iteration:987 feature:5 threshold:52 min-objective:0.942586 iteration:988 feature:6 threshold:14.5 min-objective:0.920025 iteration:989 feature:3 threshold:20.5 min-objective:0.933928 iteration:990 feature:5 threshold:59.5 min-objective:0.941098 iteration:991 feature:5 threshold:37.5 min-objective:0.953035 iteration:992 feature:6 threshold:14.5 min-objective:0.938003 iteration:993 feature:4 threshold:33.5 min-objective:0.939108 iteration:994 feature:4 threshold:23.5 min-objective:0.942623 iteration:995 feature:6 threshold:23.5 min-objective:0.934287 iteration:996 feature:5 threshold:50.5 min-objective:0.961342 iteration:997 feature:4 threshold:40.5 min-objective:0.961468 iteration:998 feature:4 threshold:37.5 min-objective:0.945635 iteration:999 feature:6 threshold:14.5 min-objective:0.954456 === END program2: ./run learn ../program1/data --- OK [1s] === END program1: ./run learn ../dataset3/train --- OK [1s] ===== MAIN: predict/evaluate on train data ===== === START program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in === END program4: ./run stripLabels ../dataset3/train ../program0/evalTrain.in --- OK [0s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out === START program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output === END program2: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out.multiclass-output --- OK [0s] === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s] === START program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out === END program5: ./run evaluate ../dataset3/train ../program0/evalTrain.out --- OK [0s] ===== MAIN: predict/evaluate on test data ===== === START program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in === END program4: ./run stripLabels ../dataset3/test ../program0/evalTest.in --- OK [0s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out === START program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output === END program2: ./run predict ../program0/evalTest.in ../program0/evalTest.out.multiclass-output --- OK [0s] === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s] === START program5: ./run evaluate ../dataset3/test ../program0/evalTest.out === END program5: ./run evaluate ../dataset3/test ../program0/evalTest.out --- OK [0s] real 0m10.460s user 0m6.952s sys 0m1.284s
Run specification 
Results
Must be logged in to post comments.