 | Run 19883 |
| Creator | internal |
| Program | minimalist-boost |
| Dataset | Simple Bio-info Glycosylation Data |
| Task type | MulticlassClassification |
| Created | 318d1h ago |
| Download | Login required! |
Done! 
| BinaryClassification | |
| 5s | |
| 0 | |
| 0s | |
| 0.023 | |
| 0s |
Log file
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(lines omitted) ... iteration:627 feature:32 threshold:-6.49234 min-objective:0.759785 iteration:628 feature:10 threshold:12.3812 min-objective:0.762129 iteration:629 feature:8 threshold:-6.77969 min-objective:0.781502 iteration:630 feature:18 threshold:12.1015 min-objective:0.797003 iteration:631 feature:55 threshold:102.466 min-objective:0.814203 iteration:632 feature:42 threshold:8.66092 min-objective:0.719651 iteration:633 feature:5 threshold:2.94061 min-objective:0.778211 iteration:634 feature:6 threshold:33.0421 min-objective:0.78469 iteration:635 feature:43 threshold:28.4061 min-objective:0.816712 iteration:636 feature:9 threshold:136.567 min-objective:0.794414 iteration:637 feature:6 threshold:8.16092 min-objective:0.821699 iteration:638 feature:31 threshold:34.0421 min-objective:0.779661 iteration:639 feature:34 threshold:11.1609 min-objective:0.702976 iteration:640 feature:28 threshold:9.94061 min-objective:0.752822 iteration:641 feature:76 threshold:23.6015 min-objective:0.796053 iteration:642 feature:56 threshold:2.66092 min-objective:0.70923 iteration:643 feature:15 threshold:-2.05939 min-objective:0.754144 iteration:644 feature:13 threshold:7.16092 min-objective:0.80932 iteration:645 feature:86 threshold:16.3812 min-objective:0.746049 iteration:646 feature:14 threshold:4.94061 min-objective:0.803533 iteration:647 feature:73 threshold:3.94061 min-objective:0.76592 iteration:648 feature:38 threshold:50.4828 min-objective:0.828233 iteration:649 feature:67 threshold:8.66092 min-objective:0.82488 iteration:650 feature:90 threshold:-6.77969 min-objective:0.810879 iteration:651 feature:56 threshold:2.66092 min-objective:0.781549 iteration:652 feature:91 threshold:34.8218 min-objective:0.667515 iteration:653 feature:29 threshold:13.6015 min-objective:0.774245 iteration:654 feature:10 threshold:7.66092 min-objective:0.784425 iteration:655 feature:46 threshold:-4.77969 min-objective:0.687734 iteration:656 feature:68 threshold:2.94061 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min-objective:0.702493 iteration:957 feature:41 threshold:10.6609 min-objective:0.746436 iteration:958 feature:31 threshold:34.0421 min-objective:0.735218 iteration:959 feature:69 threshold:15.3812 min-objective:0.603878 iteration:960 feature:95 threshold:57.9234 min-objective:0.791527 iteration:961 feature:31 threshold:-2.27969 min-objective:0.763359 iteration:962 feature:67 threshold:8.66092 min-objective:0.708361 iteration:963 feature:67 threshold:4.94061 min-objective:0.783978 iteration:964 feature:42 threshold:15.3812 min-objective:0.83172 iteration:965 feature:34 threshold:11.1609 min-objective:0.822227 iteration:966 feature:10 threshold:12.3812 min-objective:0.744465 iteration:967 feature:56 threshold:2.66092 min-objective:0.764793 iteration:968 feature:15 threshold:1.94061 min-objective:0.722656 iteration:969 feature:14 threshold:7.66092 min-objective:0.840731 iteration:970 feature:101 threshold:5.66092 min-objective:0.824768 iteration:971 feature:36 threshold:33.0421 min-objective:0.806343 iteration:972 feature:33 threshold:2.88123 min-objective:0.7594 iteration:973 feature:8 threshold:-6.77969 min-objective:0.739665 iteration:974 feature:18 threshold:12.1015 min-objective:0.757788 iteration:975 feature:55 threshold:102.466 min-objective:0.807401 iteration:976 feature:73 threshold:3.94061 min-objective:0.767076 iteration:977 feature:5 threshold:6.66092 min-objective:0.665711 iteration:978 feature:14 threshold:7.66092 min-objective:0.7591 iteration:979 feature:99 threshold:-2.33908 min-objective:0.816769 iteration:980 feature:42 threshold:8.66092 min-objective:0.735654 iteration:981 feature:86 threshold:17.6015 min-objective:0.72638 iteration:982 feature:32 threshold:-6.49234 min-objective:0.830551 iteration:983 feature:56 threshold:-3.27969 min-objective:0.849567 iteration:984 feature:91 threshold:62.9234 min-objective:0.695039 iteration:985 feature:18 threshold:16.3812 min-objective:0.709811 iteration:986 feature:38 threshold:44.7031 min-objective:0.773844 iteration:987 feature:9 threshold:53.2031 min-objective:0.768312 iteration:988 feature:56 threshold:2.66092 min-objective:0.650245 iteration:989 feature:21 threshold:15.6015 min-objective:0.781384 iteration:990 feature:102 threshold:-5.77969 min-objective:0.758957 iteration:991 feature:55 threshold:102.466 min-objective:0.779766 iteration:992 feature:10 threshold:12.3812 min-objective:0.79139 iteration:993 feature:22 threshold:51.7031 min-objective:0.775685 iteration:994 feature:31 threshold:34.0421 min-objective:0.749991 iteration:995 feature:5 threshold:6.66092 min-objective:0.719142 iteration:996 feature:68 threshold:13.8812 min-objective:0.654109 iteration:997 feature:28 threshold:12.6609 min-objective:0.77957 iteration:998 feature:56 threshold:-3.27969 min-objective:0.731519 iteration:999 feature:91 threshold:62.9234 min-objective:0.727749 === END program2: ./run learn ../program1/data --- OK [5s] === END program1: ./run learn ../dataset3/train --- OK [5s] ===== 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 [1s] === 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 0m14.966s user 0m8.113s sys 0m1.052s
Run specification 
Results
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