 | Run 7917 |
| Creator | internal |
| Program | boostexter |
| Dataset | mushroom |
| Task type | MulticlassClassification |
| Created | 31d15h ago |
| Download | Login required! |
Done! 
| 23s | |
| 38M | |
| MulticlassClassification | |
| 24s | |
| 0 | |
| 1s | |
| 0 | |
| 0s |
Log file
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0.000000 test= nan train= 0.0000000 rnd 904: wh-err= 0.843646 th-err= 0.000000 test= nan train= 0.0000000 rnd 905: wh-err= 0.911612 th-err= 0.000000 test= nan train= 0.0000000 rnd 906: wh-err= 0.875518 th-err= 0.000000 test= nan train= 0.0000000 rnd 907: wh-err= 0.883905 th-err= 0.000000 test= nan train= 0.0000000 rnd 908: wh-err= 0.837726 th-err= 0.000000 test= nan train= 0.0000000 rnd 909: wh-err= 0.835691 th-err= 0.000000 test= nan train= 0.0000000 rnd 910: wh-err= 0.893701 th-err= 0.000000 test= nan train= 0.0000000 rnd 911: wh-err= 0.897506 th-err= 0.000000 test= nan train= 0.0000000 rnd 912: wh-err= 0.887435 th-err= 0.000000 test= nan train= 0.0000000 rnd 913: wh-err= 0.870705 th-err= 0.000000 test= nan train= 0.0000000 rnd 914: wh-err= 0.817387 th-err= 0.000000 test= nan train= 0.0000000 rnd 915: wh-err= 0.859856 th-err= 0.000000 test= nan train= 0.0000000 rnd 916: wh-err= 0.895621 th-err= 0.000000 test= nan train= 0.0000000 rnd 917: wh-err= 0.904653 th-err= 0.000000 test= nan train= 0.0000000 rnd 918: wh-err= 0.840947 th-err= 0.000000 test= nan train= 0.0000000 rnd 919: wh-err= 0.796924 th-err= 0.000000 test= nan train= 0.0000000 rnd 920: wh-err= 0.853753 th-err= 0.000000 test= nan train= 0.0000000 rnd 921: wh-err= 0.890468 th-err= 0.000000 test= nan train= 0.0000000 rnd 922: wh-err= 0.890629 th-err= 0.000000 test= nan train= 0.0000000 rnd 923: wh-err= 0.898662 th-err= 0.000000 test= nan train= 0.0000000 rnd 924: wh-err= 0.870388 th-err= 0.000000 test= nan train= 0.0000000 rnd 925: wh-err= 0.871393 th-err= 0.000000 test= nan train= 0.0000000 rnd 926: wh-err= 0.862341 th-err= 0.000000 test= nan train= 0.0000000 rnd 927: wh-err= 0.865545 th-err= 0.000000 test= nan train= 0.0000000 rnd 928: wh-err= 0.810178 th-err= 0.000000 test= nan train= 0.0000000 rnd 929: wh-err= 0.880918 th-err= 0.000000 test= nan train= 0.0000000 rnd 930: wh-err= 0.846445 th-err= 0.000000 test= nan train= 0.0000000 rnd 931: wh-err= 0.823936 th-err= 0.000000 test= nan train= 0.0000000 rnd 932: wh-err= 0.804113 th-err= 0.000000 test= nan train= 0.0000000 rnd 933: wh-err= 0.864329 th-err= 0.000000 test= nan train= 0.0000000 rnd 934: wh-err= 0.895043 th-err= 0.000000 test= nan train= 0.0000000 rnd 935: wh-err= 0.882843 th-err= 0.000000 test= nan train= 0.0000000 rnd 936: wh-err= 0.808716 th-err= 0.000000 test= nan train= 0.0000000 rnd 937: wh-err= 0.821426 th-err= 0.000000 test= nan train= 0.0000000 rnd 938: wh-err= 0.899379 th-err= 0.000000 test= nan train= 0.0000000 rnd 939: wh-err= 0.880976 th-err= 0.000000 test= nan train= 0.0000000 rnd 940: wh-err= 0.886477 th-err= 0.000000 test= nan train= 0.0000000 rnd 941: wh-err= 0.887442 th-err= 0.000000 test= nan train= 0.0000000 rnd 942: wh-err= 0.860183 th-err= 0.000000 test= nan train= 0.0000000 rnd 943: wh-err= 0.862944 th-err= 0.000000 test= nan train= 0.0000000 rnd 944: wh-err= 0.909062 th-err= 0.000000 test= nan train= 0.0000000 rnd 945: wh-err= 0.892524 th-err= 0.000000 test= nan train= 0.0000000 rnd 946: wh-err= 0.879900 th-err= 0.000000 test= nan train= 0.0000000 rnd 947: wh-err= 0.746161 th-err= 0.000000 test= nan train= 0.0000000 rnd 948: wh-err= 0.837744 th-err= 0.000000 test= nan train= 0.0000000 rnd 949: wh-err= 0.823351 th-err= 0.000000 test= nan train= 0.0000000 rnd 950: wh-err= 0.900594 th-err= 0.000000 test= nan train= 0.0000000 rnd 951: wh-err= 0.847558 th-err= 0.000000 test= nan train= 0.0000000 rnd 952: wh-err= 0.883459 th-err= 0.000000 test= nan train= 0.0000000 rnd 953: wh-err= 0.882595 th-err= 0.000000 test= nan train= 0.0000000 rnd 954: wh-err= 0.893639 th-err= 0.000000 test= nan train= 0.0000000 rnd 955: wh-err= 0.852220 th-err= 0.000000 test= nan train= 0.0000000 rnd 956: wh-err= 0.877605 th-err= 0.000000 test= nan train= 0.0000000 rnd 957: wh-err= 0.843772 th-err= 0.000000 test= nan train= 0.0000000 rnd 958: wh-err= 0.903231 th-err= 0.000000 test= nan train= 0.0000000 rnd 959: wh-err= 0.863371 th-err= 0.000000 test= nan train= 0.0000000 rnd 960: wh-err= 0.828596 th-err= 0.000000 test= nan train= 0.0000000 rnd 961: wh-err= 0.872200 th-err= 0.000000 test= nan train= 0.0000000 rnd 962: wh-err= 0.877720 th-err= 0.000000 test= nan train= 0.0000000 rnd 963: wh-err= 0.858510 th-err= 0.000000 test= nan train= 0.0000000 rnd 964: wh-err= 0.780026 th-err= 0.000000 test= nan train= 0.0000000 rnd 965: wh-err= 0.847829 th-err= 0.000000 test= nan train= 0.0000000 rnd 966: wh-err= 0.923625 th-err= 0.000000 test= nan train= 0.0000000 rnd 967: wh-err= 0.920297 th-err= 0.000000 test= nan train= 0.0000000 rnd 968: wh-err= 0.907487 th-err= 0.000000 test= nan train= 0.0000000 rnd 969: wh-err= 0.906446 th-err= 0.000000 test= nan train= 0.0000000 rnd 970: wh-err= 0.890036 th-err= 0.000000 test= nan train= 0.0000000 rnd 971: wh-err= 0.879207 th-err= 0.000000 test= nan train= 0.0000000 rnd 972: wh-err= 0.858890 th-err= 0.000000 test= nan train= 0.0000000 rnd 973: wh-err= 0.846972 th-err= 0.000000 test= nan train= 0.0000000 rnd 974: wh-err= 0.910530 th-err= 0.000000 test= nan train= 0.0000000 rnd 975: wh-err= 0.890229 th-err= 0.000000 test= nan train= 0.0000000 rnd 976: wh-err= 0.878998 th-err= 0.000000 test= nan train= 0.0000000 rnd 977: wh-err= 0.852687 th-err= 0.000000 test= nan train= 0.0000000 rnd 978: wh-err= 0.896806 th-err= 0.000000 test= nan train= 0.0000000 rnd 979: wh-err= 0.838677 th-err= 0.000000 test= nan train= 0.0000000 rnd 980: wh-err= 0.856073 th-err= 0.000000 test= nan train= 0.0000000 rnd 981: wh-err= 0.843087 th-err= 0.000000 test= nan train= 0.0000000 rnd 982: wh-err= 0.863147 th-err= 0.000000 test= nan train= 0.0000000 rnd 983: wh-err= 0.844500 th-err= 0.000000 test= nan train= 0.0000000 rnd 984: wh-err= 0.919886 th-err= 0.000000 test= nan train= 0.0000000 rnd 985: wh-err= 0.866690 th-err= 0.000000 test= nan train= 0.0000000 rnd 986: wh-err= 0.924254 th-err= 0.000000 test= nan train= 0.0000000 rnd 987: wh-err= 0.889832 th-err= 0.000000 test= nan train= 0.0000000 rnd 988: wh-err= 0.873868 th-err= 0.000000 test= nan train= 0.0000000 rnd 989: wh-err= 0.867327 th-err= 0.000000 test= nan train= 0.0000000 rnd 990: wh-err= 0.844905 th-err= 0.000000 test= nan train= 0.0000000 rnd 991: wh-err= 0.879421 th-err= 0.000000 test= nan train= 0.0000000 rnd 992: wh-err= 0.899243 th-err= 0.000000 test= nan train= 0.0000000 rnd 993: wh-err= 0.873581 th-err= 0.000000 test= nan train= 0.0000000 rnd 994: wh-err= 0.823089 th-err= 0.000000 test= nan train= 0.0000000 rnd 995: wh-err= 0.857610 th-err= 0.000000 test= nan train= 0.0000000 rnd 996: wh-err= 0.858396 th-err= 0.000000 test= nan train= 0.0000000 rnd 997: wh-err= 0.883475 th-err= 0.000000 test= nan train= 0.0000000 rnd 998: wh-err= 0.860660 th-err= 0.000000 test= nan train= 0.0000000 rnd 999: wh-err= 0.865611 th-err= 0.000000 test= nan train= 0.0000000 rnd 1000: wh-err= 0.907810 th-err= 0.000000 test= nan train= 0.0000000 === END program1: ./run learn ../dataset2/train --- OK [24s] ===== 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 = 5687.000000 / 5687 = 1.000000 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s] ===== 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 = 2437.000000 / 2437 = 1.000000 === 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 0m27.557s user 0m10.061s sys 0m0.160s
Run specification 
Results
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