 | Run 14337 |
| Creator | internal |
| Program | minimalist-boost |
| Dataset | Easy |
| Task type | MulticlassClassification |
| Created | 28d17h ago |
| Download | Login required! |
Done! 
| 2s | |
| 74M | |
| MulticlassClassification | |
| 1s | |
| 0 | |
| 0s | |
| 0.029 | |
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Log file
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(lines omitted) ... iteration:622 feature:1 threshold:5.13932 min-objective:0.884878 iteration:623 feature:2 threshold:7.53757 min-objective:0.826351 iteration:624 feature:1 threshold:8.44576 min-objective:0.765465 iteration:625 feature:2 threshold:5.00289 min-objective:0.888072 iteration:626 feature:2 threshold:7.53757 min-objective:0.855335 iteration:627 feature:1 threshold:5.13384 min-objective:0.824443 iteration:628 feature:2 threshold:9.47611 min-objective:0.829052 iteration:629 feature:2 threshold:5.00289 min-objective:0.903305 iteration:630 feature:1 threshold:5.13932 min-objective:0.884877 iteration:631 feature:2 threshold:7.53757 min-objective:0.826351 iteration:632 feature:1 threshold:6.81359 min-objective:0.765466 iteration:633 feature:2 threshold:5.00289 min-objective:0.888072 iteration:634 feature:2 threshold:7.53757 min-objective:0.855335 iteration:635 feature:1 threshold:5.13384 min-objective:0.824443 iteration:636 feature:2 threshold:9.47611 min-objective:0.829052 iteration:637 feature:2 threshold:5.00289 min-objective:0.903305 iteration:638 feature:1 threshold:4.63949 min-objective:0.884878 iteration:639 feature:2 threshold:7.53757 min-objective:0.826351 iteration:640 feature:1 threshold:8.44576 min-objective:0.765465 iteration:641 feature:2 threshold:5.00289 min-objective:0.888073 iteration:642 feature:2 threshold:7.53757 min-objective:0.855335 iteration:643 feature:1 threshold:5.13384 min-objective:0.824443 iteration:644 feature:2 threshold:9.47611 min-objective:0.829052 iteration:645 feature:2 threshold:5.00289 min-objective:0.903305 iteration:646 feature:1 threshold:5.13932 min-objective:0.884877 iteration:647 feature:2 threshold:7.53757 min-objective:0.826352 iteration:648 feature:1 threshold:6.81359 min-objective:0.765466 iteration:649 feature:2 threshold:5.00289 min-objective:0.888072 iteration:650 feature:2 threshold:7.53757 min-objective:0.855335 iteration:651 feature:1 threshold:5.69861 min-objective:0.824443 iteration:652 feature:2 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min-objective:0.826355 iteration:944 feature:1 threshold:8.44576 min-objective:0.765466 iteration:945 feature:2 threshold:5.00289 min-objective:0.88807 iteration:946 feature:2 threshold:7.53757 min-objective:0.855338 iteration:947 feature:1 threshold:5.70946 min-objective:0.824444 iteration:948 feature:2 threshold:9.47611 min-objective:0.829052 iteration:949 feature:2 threshold:5.00289 min-objective:0.903303 iteration:950 feature:1 threshold:5.69861 min-objective:0.884878 iteration:951 feature:2 threshold:7.53757 min-objective:0.826355 iteration:952 feature:1 threshold:6.81359 min-objective:0.765467 iteration:953 feature:2 threshold:5.00289 min-objective:0.88807 iteration:954 feature:2 threshold:7.53757 min-objective:0.855338 iteration:955 feature:1 threshold:5.13384 min-objective:0.824444 iteration:956 feature:2 threshold:9.47611 min-objective:0.829052 iteration:957 feature:2 threshold:5.00289 min-objective:0.903303 iteration:958 feature:1 threshold:4.63949 min-objective:0.884878 iteration:959 feature:2 threshold:7.53757 min-objective:0.826355 iteration:960 feature:1 threshold:8.44576 min-objective:0.765467 iteration:961 feature:2 threshold:5.00289 min-objective:0.88807 iteration:962 feature:2 threshold:7.53757 min-objective:0.855338 iteration:963 feature:1 threshold:5.42062 min-objective:0.824444 iteration:964 feature:2 threshold:9.47611 min-objective:0.829052 iteration:965 feature:2 threshold:5.00289 min-objective:0.903303 iteration:966 feature:1 threshold:5.13384 min-objective:0.884878 iteration:967 feature:2 threshold:7.53757 min-objective:0.826355 iteration:968 feature:1 threshold:6.81359 min-objective:0.765467 iteration:969 feature:2 threshold:5.00289 min-objective:0.88807 iteration:970 feature:2 threshold:7.53757 min-objective:0.855338 iteration:971 feature:1 threshold:5.69861 min-objective:0.824444 iteration:972 feature:2 threshold:9.47611 min-objective:0.829052 iteration:973 feature:2 threshold:5.00289 min-objective:0.903303 iteration:974 feature:1 threshold:5.13932 min-objective:0.884878 iteration:975 feature:2 threshold:7.53757 min-objective:0.826355 iteration:976 feature:1 threshold:8.44576 min-objective:0.765467 iteration:977 feature:2 threshold:5.00289 min-objective:0.88807 iteration:978 feature:2 threshold:7.53757 min-objective:0.855338 iteration:979 feature:1 threshold:5.70946 min-objective:0.824444 iteration:980 feature:2 threshold:9.47611 min-objective:0.829052 iteration:981 feature:2 threshold:5.00289 min-objective:0.903303 iteration:982 feature:1 threshold:5.69861 min-objective:0.884878 iteration:983 feature:2 threshold:7.53757 min-objective:0.826355 iteration:984 feature:1 threshold:6.81359 min-objective:0.765467 iteration:985 feature:2 threshold:5.00289 min-objective:0.88807 iteration:986 feature:2 threshold:7.53757 min-objective:0.855338 iteration:987 feature:1 threshold:5.13384 min-objective:0.824444 iteration:988 feature:2 threshold:9.47611 min-objective:0.829052 iteration:989 feature:2 threshold:5.00289 min-objective:0.903303 iteration:990 feature:1 threshold:4.63949 min-objective:0.884878 iteration:991 feature:2 threshold:7.53757 min-objective:0.826355 iteration:992 feature:1 threshold:8.44576 min-objective:0.765467 iteration:993 feature:2 threshold:5.00289 min-objective:0.88807 iteration:994 feature:2 threshold:7.53757 min-objective:0.855338 iteration:995 feature:1 threshold:5.42062 min-objective:0.824444 iteration:996 feature:2 threshold:9.47611 min-objective:0.829052 iteration:997 feature:2 threshold:5.00289 min-objective:0.903303 iteration:998 feature:1 threshold:5.13384 min-objective:0.884878 iteration:999 feature:2 threshold:7.53757 min-objective:0.826355 === END program1: ./run learn ../dataset2/train --- OK [1s] ===== 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 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s] === 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 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s] real 0m9.457s user 0m8.097s sys 0m1.196s
Run specification 
Results
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