 | Run 7972 |
| Creator | internal |
| Program | boostexter |
| Dataset | lung-cancer |
| Task type | MulticlassClassification |
| Created | 1y122d ago |
| Download | Login required! |
Done! 
| 1s | |
| 31M | |
| MulticlassClassification | |
| 0 | |
| 0.400 | |
Log file
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0.000000 test= nan train= 0.0000000 rnd 904: wh-err= 0.882219 th-err= 0.000000 test= nan train= 0.0000000 rnd 905: wh-err= 0.897749 th-err= 0.000000 test= nan train= 0.0000000 rnd 906: wh-err= 0.898946 th-err= 0.000000 test= nan train= 0.0000000 rnd 907: wh-err= 0.913288 th-err= 0.000000 test= nan train= 0.0000000 rnd 908: wh-err= 0.895609 th-err= 0.000000 test= nan train= 0.0000000 rnd 909: wh-err= 0.907969 th-err= 0.000000 test= nan train= 0.0000000 rnd 910: wh-err= 0.922235 th-err= 0.000000 test= nan train= 0.0000000 rnd 911: wh-err= 0.882749 th-err= 0.000000 test= nan train= 0.0000000 rnd 912: wh-err= 0.905738 th-err= 0.000000 test= nan train= 0.0000000 rnd 913: wh-err= 0.912973 th-err= 0.000000 test= nan train= 0.0000000 rnd 914: wh-err= 0.925363 th-err= 0.000000 test= nan train= 0.0000000 rnd 915: wh-err= 0.897913 th-err= 0.000000 test= nan train= 0.0000000 rnd 916: wh-err= 0.923614 th-err= 0.000000 test= nan train= 0.0000000 rnd 917: wh-err= 0.881234 th-err= 0.000000 test= nan train= 0.0000000 rnd 918: wh-err= 0.898129 th-err= 0.000000 test= nan train= 0.0000000 rnd 919: wh-err= 0.928165 th-err= 0.000000 test= nan train= 0.0000000 rnd 920: wh-err= 0.908827 th-err= 0.000000 test= nan train= 0.0000000 rnd 921: wh-err= 0.869544 th-err= 0.000000 test= nan train= 0.0000000 rnd 922: wh-err= 0.882619 th-err= 0.000000 test= nan train= 0.0000000 rnd 923: wh-err= 0.881507 th-err= 0.000000 test= nan train= 0.0000000 rnd 924: wh-err= 0.893693 th-err= 0.000000 test= nan train= 0.0000000 rnd 925: wh-err= 0.903394 th-err= 0.000000 test= nan train= 0.0000000 rnd 926: wh-err= 0.905859 th-err= 0.000000 test= nan train= 0.0000000 rnd 927: wh-err= 0.942620 th-err= 0.000000 test= nan train= 0.0000000 rnd 928: wh-err= 0.908150 th-err= 0.000000 test= nan train= 0.0000000 rnd 929: wh-err= 0.909075 th-err= 0.000000 test= nan train= 0.0000000 rnd 930: wh-err= 0.913505 th-err= 0.000000 test= nan train= 0.0000000 rnd 931: wh-err= 0.867532 th-err= 0.000000 test= nan train= 0.0000000 rnd 932: wh-err= 0.907883 th-err= 0.000000 test= nan train= 0.0000000 rnd 933: wh-err= 0.879854 th-err= 0.000000 test= nan train= 0.0000000 rnd 934: wh-err= 0.857150 th-err= 0.000000 test= nan train= 0.0000000 rnd 935: wh-err= 0.883126 th-err= 0.000000 test= nan train= 0.0000000 rnd 936: wh-err= 0.924760 th-err= 0.000000 test= nan train= 0.0000000 rnd 937: wh-err= 0.888212 th-err= 0.000000 test= nan train= 0.0000000 rnd 938: wh-err= 0.900816 th-err= 0.000000 test= nan train= 0.0000000 rnd 939: wh-err= 0.906177 th-err= 0.000000 test= nan train= 0.0000000 rnd 940: wh-err= 0.856500 th-err= 0.000000 test= nan train= 0.0000000 rnd 941: wh-err= 0.877286 th-err= 0.000000 test= nan train= 0.0000000 rnd 942: wh-err= 0.916157 th-err= 0.000000 test= nan train= 0.0000000 rnd 943: wh-err= 0.914311 th-err= 0.000000 test= nan train= 0.0000000 rnd 944: wh-err= 0.893513 th-err= 0.000000 test= nan train= 0.0000000 rnd 945: wh-err= 0.903596 th-err= 0.000000 test= nan train= 0.0000000 rnd 946: wh-err= 0.904310 th-err= 0.000000 test= nan train= 0.0000000 rnd 947: wh-err= 0.887055 th-err= 0.000000 test= nan train= 0.0000000 rnd 948: wh-err= 0.925547 th-err= 0.000000 test= nan train= 0.0000000 rnd 949: wh-err= 0.913055 th-err= 0.000000 test= nan train= 0.0000000 rnd 950: wh-err= 0.861416 th-err= 0.000000 test= nan train= 0.0000000 rnd 951: wh-err= 0.882663 th-err= 0.000000 test= nan train= 0.0000000 rnd 952: wh-err= 0.874540 th-err= 0.000000 test= nan train= 0.0000000 rnd 953: wh-err= 0.932572 th-err= 0.000000 test= nan train= 0.0000000 rnd 954: wh-err= 0.900672 th-err= 0.000000 test= nan train= 0.0000000 rnd 955: wh-err= 0.919339 th-err= 0.000000 test= nan train= 0.0000000 rnd 956: wh-err= 0.896016 th-err= 0.000000 test= nan train= 0.0000000 rnd 957: wh-err= 0.891708 th-err= 0.000000 test= nan train= 0.0000000 rnd 958: wh-err= 0.874922 th-err= 0.000000 test= nan train= 0.0000000 rnd 959: wh-err= 0.891513 th-err= 0.000000 test= nan train= 0.0000000 rnd 960: wh-err= 0.892583 th-err= 0.000000 test= nan train= 0.0000000 rnd 961: wh-err= 0.894463 th-err= 0.000000 test= nan train= 0.0000000 rnd 962: wh-err= 0.897786 th-err= 0.000000 test= nan train= 0.0000000 rnd 963: wh-err= 0.898955 th-err= 0.000000 test= nan train= 0.0000000 rnd 964: wh-err= 0.913007 th-err= 0.000000 test= nan train= 0.0000000 rnd 965: wh-err= 0.914520 th-err= 0.000000 test= nan train= 0.0000000 rnd 966: wh-err= 0.886928 th-err= 0.000000 test= nan train= 0.0000000 rnd 967: wh-err= 0.891689 th-err= 0.000000 test= nan train= 0.0000000 rnd 968: wh-err= 0.924460 th-err= 0.000000 test= nan train= 0.0000000 rnd 969: wh-err= 0.925916 th-err= 0.000000 test= nan train= 0.0000000 rnd 970: wh-err= 0.899294 th-err= 0.000000 test= nan train= 0.0000000 rnd 971: wh-err= 0.924657 th-err= 0.000000 test= nan train= 0.0000000 rnd 972: wh-err= 0.903382 th-err= 0.000000 test= nan train= 0.0000000 rnd 973: wh-err= 0.909079 th-err= 0.000000 test= nan train= 0.0000000 rnd 974: wh-err= 0.862415 th-err= 0.000000 test= nan train= 0.0000000 rnd 975: wh-err= 0.892908 th-err= 0.000000 test= nan train= 0.0000000 rnd 976: wh-err= 0.897340 th-err= 0.000000 test= nan train= 0.0000000 rnd 977: wh-err= 0.913240 th-err= 0.000000 test= nan train= 0.0000000 rnd 978: wh-err= 0.909019 th-err= 0.000000 test= nan train= 0.0000000 rnd 979: wh-err= 0.909799 th-err= 0.000000 test= nan train= 0.0000000 rnd 980: wh-err= 0.860017 th-err= 0.000000 test= nan train= 0.0000000 rnd 981: wh-err= 0.898152 th-err= 0.000000 test= nan train= 0.0000000 rnd 982: wh-err= 0.915957 th-err= 0.000000 test= nan train= 0.0000000 rnd 983: wh-err= 0.934548 th-err= 0.000000 test= nan train= 0.0000000 rnd 984: wh-err= 0.932923 th-err= 0.000000 test= nan train= 0.0000000 rnd 985: wh-err= 0.877997 th-err= 0.000000 test= nan train= 0.0000000 rnd 986: wh-err= 0.915036 th-err= 0.000000 test= nan train= 0.0000000 rnd 987: wh-err= 0.898877 th-err= 0.000000 test= nan train= 0.0000000 rnd 988: wh-err= 0.880003 th-err= 0.000000 test= nan train= 0.0000000 rnd 989: wh-err= 0.888017 th-err= 0.000000 test= nan train= 0.0000000 rnd 990: wh-err= 0.911484 th-err= 0.000000 test= nan train= 0.0000000 rnd 991: wh-err= 0.927574 th-err= 0.000000 test= nan train= 0.0000000 rnd 992: wh-err= 0.880739 th-err= 0.000000 test= nan train= 0.0000000 rnd 993: wh-err= 0.885341 th-err= 0.000000 test= nan train= 0.0000000 rnd 994: wh-err= 0.889998 th-err= 0.000000 test= nan train= 0.0000000 rnd 995: wh-err= 0.933689 th-err= 0.000000 test= nan train= 0.0000000 rnd 996: wh-err= 0.890000 th-err= 0.000000 test= nan train= 0.0000000 rnd 997: wh-err= 0.901491 th-err= 0.000000 test= nan train= 0.0000000 rnd 998: wh-err= 0.911912 th-err= 0.000000 test= nan train= 0.0000000 rnd 999: wh-err= 0.908922 th-err= 0.000000 test= nan train= 0.0000000 rnd 1000: wh-err= 0.916359 th-err= 0.000000 test= nan train= 0.0000000 === END program1: ./run learn ../dataset2/train --- OK [0s] ===== 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 Copyright 2001 AT&T. All rights reserved. Test error = 22.000000 / 22 = 1.000000 === 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 Copyright 2001 AT&T. All rights reserved. Test error = 10.000000 / 10 = 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 [1s] real 0m1.324s user 0m0.408s sys 0m0.120s
Run specification 
Results
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