 | Run 12292 |
| Creator | yorinasub17 |
| Program | boostexter |
| Dataset | image |
| Task type | MulticlassClassification |
| Created | 28d16h ago |
| Download | Login required! |
Done! 
| 5s | |
| 38M | |
| MulticlassClassification | |
| 4s | |
| 0 | |
| 0s | |
| 0.050 | |
| 1s |
Log file
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0.000000 test= nan train= 0.0000000 rnd 904: wh-err= 0.951699 th-err= 0.000000 test= nan train= 0.0000000 rnd 905: wh-err= 0.940157 th-err= 0.000000 test= nan train= 0.0000000 rnd 906: wh-err= 0.938682 th-err= 0.000000 test= nan train= 0.0000000 rnd 907: wh-err= 0.942493 th-err= 0.000000 test= nan train= 0.0000000 rnd 908: wh-err= 0.929407 th-err= 0.000000 test= nan train= 0.0000000 rnd 909: wh-err= 0.945459 th-err= 0.000000 test= nan train= 0.0000000 rnd 910: wh-err= 0.944074 th-err= 0.000000 test= nan train= 0.0000000 rnd 911: wh-err= 0.935758 th-err= 0.000000 test= nan train= 0.0000000 rnd 912: wh-err= 0.954448 th-err= 0.000000 test= nan train= 0.0000000 rnd 913: wh-err= 0.946134 th-err= 0.000000 test= nan train= 0.0000000 rnd 914: wh-err= 0.951305 th-err= 0.000000 test= nan train= 0.0000000 rnd 915: wh-err= 0.941956 th-err= 0.000000 test= nan train= 0.0000000 rnd 916: wh-err= 0.932120 th-err= 0.000000 test= nan train= 0.0000000 rnd 917: wh-err= 0.941049 th-err= 0.000000 test= nan train= 0.0000000 rnd 918: wh-err= 0.937626 th-err= 0.000000 test= nan train= 0.0000000 rnd 919: wh-err= 0.940195 th-err= 0.000000 test= nan train= 0.0000000 rnd 920: wh-err= 0.951974 th-err= 0.000000 test= nan train= 0.0000000 rnd 921: wh-err= 0.949654 th-err= 0.000000 test= nan train= 0.0000000 rnd 922: wh-err= 0.953731 th-err= 0.000000 test= nan train= 0.0000000 rnd 923: wh-err= 0.933779 th-err= 0.000000 test= nan train= 0.0000000 rnd 924: wh-err= 0.937197 th-err= 0.000000 test= nan train= 0.0000000 rnd 925: wh-err= 0.929412 th-err= 0.000000 test= nan train= 0.0000000 rnd 926: wh-err= 0.952159 th-err= 0.000000 test= nan train= 0.0000000 rnd 927: wh-err= 0.954152 th-err= 0.000000 test= nan train= 0.0000000 rnd 928: wh-err= 0.946288 th-err= 0.000000 test= nan train= 0.0000000 rnd 929: wh-err= 0.955823 th-err= 0.000000 test= nan train= 0.0000000 rnd 930: wh-err= 0.940001 th-err= 0.000000 test= nan train= 0.0000000 rnd 931: wh-err= 0.948211 th-err= 0.000000 test= nan train= 0.0000000 rnd 932: wh-err= 0.948330 th-err= 0.000000 test= nan train= 0.0000000 rnd 933: wh-err= 0.935185 th-err= 0.000000 test= nan train= 0.0000000 rnd 934: wh-err= 0.943430 th-err= 0.000000 test= nan train= 0.0000000 rnd 935: wh-err= 0.943825 th-err= 0.000000 test= nan train= 0.0000000 rnd 936: wh-err= 0.946509 th-err= 0.000000 test= nan train= 0.0000000 rnd 937: wh-err= 0.947870 th-err= 0.000000 test= nan train= 0.0000000 rnd 938: wh-err= 0.949344 th-err= 0.000000 test= nan train= 0.0000000 rnd 939: wh-err= 0.954906 th-err= 0.000000 test= nan train= 0.0000000 rnd 940: wh-err= 0.952617 th-err= 0.000000 test= nan train= 0.0000000 rnd 941: wh-err= 0.944857 th-err= 0.000000 test= nan train= 0.0000000 rnd 942: wh-err= 0.948500 th-err= 0.000000 test= nan train= 0.0000000 rnd 943: wh-err= 0.949185 th-err= 0.000000 test= nan train= 0.0000000 rnd 944: wh-err= 0.939284 th-err= 0.000000 test= nan train= 0.0000000 rnd 945: wh-err= 0.935096 th-err= 0.000000 test= nan train= 0.0000000 rnd 946: wh-err= 0.928485 th-err= 0.000000 test= nan train= 0.0000000 rnd 947: wh-err= 0.929924 th-err= 0.000000 test= nan train= 0.0000000 rnd 948: wh-err= 0.932832 th-err= 0.000000 test= nan train= 0.0000000 rnd 949: wh-err= 0.942685 th-err= 0.000000 test= nan train= 0.0000000 rnd 950: wh-err= 0.922016 th-err= 0.000000 test= nan train= 0.0000000 rnd 951: wh-err= 0.946493 th-err= 0.000000 test= nan train= 0.0000000 rnd 952: wh-err= 0.928496 th-err= 0.000000 test= nan train= 0.0000000 rnd 953: wh-err= 0.929793 th-err= 0.000000 test= nan train= 0.0000000 rnd 954: wh-err= 0.941354 th-err= 0.000000 test= nan train= 0.0000000 rnd 955: wh-err= 0.934150 th-err= 0.000000 test= nan train= 0.0000000 rnd 956: wh-err= 0.940853 th-err= 0.000000 test= nan train= 0.0000000 rnd 957: wh-err= 0.944615 th-err= 0.000000 test= nan train= 0.0000000 rnd 958: wh-err= 0.939882 th-err= 0.000000 test= nan train= 0.0000000 rnd 959: wh-err= 0.953275 th-err= 0.000000 test= nan train= 0.0000000 rnd 960: wh-err= 0.932901 th-err= 0.000000 test= nan train= 0.0000000 rnd 961: wh-err= 0.937134 th-err= 0.000000 test= nan train= 0.0000000 rnd 962: wh-err= 0.951282 th-err= 0.000000 test= nan train= 0.0000000 rnd 963: wh-err= 0.939546 th-err= 0.000000 test= nan train= 0.0000000 rnd 964: wh-err= 0.942671 th-err= 0.000000 test= nan train= 0.0000000 rnd 965: wh-err= 0.943340 th-err= 0.000000 test= nan train= 0.0000000 rnd 966: wh-err= 0.947978 th-err= 0.000000 test= nan train= 0.0000000 rnd 967: wh-err= 0.945716 th-err= 0.000000 test= nan train= 0.0000000 rnd 968: wh-err= 0.947604 th-err= 0.000000 test= nan train= 0.0000000 rnd 969: wh-err= 0.931110 th-err= 0.000000 test= nan train= 0.0000000 rnd 970: wh-err= 0.949479 th-err= 0.000000 test= nan train= 0.0000000 rnd 971: wh-err= 0.949606 th-err= 0.000000 test= nan train= 0.0000000 rnd 972: wh-err= 0.951651 th-err= 0.000000 test= nan train= 0.0000000 rnd 973: wh-err= 0.956292 th-err= 0.000000 test= nan train= 0.0000000 rnd 974: wh-err= 0.946493 th-err= 0.000000 test= nan train= 0.0000000 rnd 975: wh-err= 0.948480 th-err= 0.000000 test= nan train= 0.0000000 rnd 976: wh-err= 0.942825 th-err= 0.000000 test= nan train= 0.0000000 rnd 977: wh-err= 0.953596 th-err= 0.000000 test= nan train= 0.0000000 rnd 978: wh-err= 0.946939 th-err= 0.000000 test= nan train= 0.0000000 rnd 979: wh-err= 0.947253 th-err= 0.000000 test= nan train= 0.0000000 rnd 980: wh-err= 0.931987 th-err= 0.000000 test= nan train= 0.0000000 rnd 981: wh-err= 0.938060 th-err= 0.000000 test= nan train= 0.0000000 rnd 982: wh-err= 0.931101 th-err= 0.000000 test= nan train= 0.0000000 rnd 983: wh-err= 0.943687 th-err= 0.000000 test= nan train= 0.0000000 rnd 984: wh-err= 0.925435 th-err= 0.000000 test= nan train= 0.0000000 rnd 985: wh-err= 0.937172 th-err= 0.000000 test= nan train= 0.0000000 rnd 986: wh-err= 0.948859 th-err= 0.000000 test= nan train= 0.0000000 rnd 987: wh-err= 0.934624 th-err= 0.000000 test= nan train= 0.0000000 rnd 988: wh-err= 0.923560 th-err= 0.000000 test= nan train= 0.0000000 rnd 989: wh-err= 0.948657 th-err= 0.000000 test= nan train= 0.0000000 rnd 990: wh-err= 0.954795 th-err= 0.000000 test= nan train= 0.0000000 rnd 991: wh-err= 0.962654 th-err= 0.000000 test= nan train= 0.0000000 rnd 992: wh-err= 0.947501 th-err= 0.000000 test= nan train= 0.0000000 rnd 993: wh-err= 0.944421 th-err= 0.000000 test= nan train= 0.0000000 rnd 994: wh-err= 0.954329 th-err= 0.000000 test= nan train= 0.0000000 rnd 995: wh-err= 0.943338 th-err= 0.000000 test= nan train= 0.0000000 rnd 996: wh-err= 0.933790 th-err= 0.000000 test= nan train= 0.0000000 rnd 997: wh-err= 0.943393 th-err= 0.000000 test= nan train= 0.0000000 rnd 998: wh-err= 0.953685 th-err= 0.000000 test= nan train= 0.0000000 rnd 999: wh-err= 0.945687 th-err= 0.000000 test= nan train= 0.0000000 rnd 1000: wh-err= 0.946955 th-err= 0.000000 test= nan train= 0.0000000 === END program1: ./run learn ../dataset2/train --- OK [4s] ===== 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 = 210.000000 / 210 = 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 = 2100.000000 / 2100 = 1.000000 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 0m5.576s user 0m1.864s sys 0m0.116s
Run specification 
Results
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