 | Run 7992 |
| Creator | internal |
| Program | boostexter |
| Dataset | new york traffic 2008 6pm |
| Task type | MulticlassClassification |
| Created | 1y122d ago |
| Download | Login required! |
Done! 
| 4s | |
| 32M | |
| MulticlassClassification | |
| 0 | |
| 0.036 | |
Log file
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0.000000 test= nan train= 0.0000000 rnd 904: wh-err= 0.698808 th-err= 0.000000 test= nan train= 0.0000000 rnd 905: wh-err= 0.817364 th-err= 0.000000 test= nan train= 0.0000000 rnd 906: wh-err= 0.755308 th-err= 0.000000 test= nan train= 0.0000000 rnd 907: wh-err= 0.707163 th-err= 0.000000 test= nan train= 0.0000000 rnd 908: wh-err= 0.756536 th-err= 0.000000 test= nan train= 0.0000000 rnd 909: wh-err= 0.787429 th-err= 0.000000 test= nan train= 0.0000000 rnd 910: wh-err= 0.691406 th-err= 0.000000 test= nan train= 0.0000000 rnd 911: wh-err= 0.686661 th-err= 0.000000 test= nan train= 0.0000000 rnd 912: wh-err= 0.536421 th-err= 0.000000 test= nan train= 0.0000000 rnd 913: wh-err= 0.701895 th-err= 0.000000 test= nan train= 0.0000000 rnd 914: wh-err= 0.774179 th-err= 0.000000 test= nan train= 0.0000000 rnd 915: wh-err= 0.623994 th-err= 0.000000 test= nan train= 0.0000000 rnd 916: wh-err= 0.706663 th-err= 0.000000 test= nan train= 0.0000000 rnd 917: wh-err= 0.663321 th-err= 0.000000 test= nan train= 0.0000000 rnd 918: wh-err= 0.685108 th-err= 0.000000 test= nan train= 0.0000000 rnd 919: wh-err= 0.837204 th-err= 0.000000 test= nan train= 0.0000000 rnd 920: wh-err= 0.770820 th-err= 0.000000 test= nan train= 0.0000000 rnd 921: wh-err= 0.810152 th-err= 0.000000 test= nan train= 0.0000000 rnd 922: wh-err= 0.656258 th-err= 0.000000 test= nan train= 0.0000000 rnd 923: wh-err= 0.752464 th-err= 0.000000 test= nan train= 0.0000000 rnd 924: wh-err= 0.645297 th-err= 0.000000 test= nan train= 0.0000000 rnd 925: wh-err= 0.815008 th-err= 0.000000 test= nan train= 0.0000000 rnd 926: wh-err= 0.682270 th-err= 0.000000 test= nan train= 0.0000000 rnd 927: wh-err= 0.738072 th-err= 0.000000 test= nan train= 0.0000000 rnd 928: wh-err= 0.739625 th-err= 0.000000 test= nan train= 0.0000000 rnd 929: wh-err= 0.747121 th-err= 0.000000 test= nan train= 0.0000000 rnd 930: wh-err= 0.771925 th-err= 0.000000 test= nan train= 0.0000000 rnd 931: wh-err= 0.686524 th-err= 0.000000 test= nan train= 0.0000000 rnd 932: wh-err= 0.751981 th-err= 0.000000 test= nan train= 0.0000000 rnd 933: wh-err= 0.597376 th-err= 0.000000 test= nan train= 0.0000000 rnd 934: wh-err= 0.701407 th-err= 0.000000 test= nan train= 0.0000000 rnd 935: wh-err= 0.642634 th-err= 0.000000 test= nan train= 0.0000000 rnd 936: wh-err= 0.696860 th-err= 0.000000 test= nan train= 0.0000000 rnd 937: wh-err= 0.785261 th-err= 0.000000 test= nan train= 0.0000000 rnd 938: wh-err= 0.708882 th-err= 0.000000 test= nan train= 0.0000000 rnd 939: wh-err= 0.760105 th-err= 0.000000 test= nan train= 0.0000000 rnd 940: wh-err= 0.802995 th-err= 0.000000 test= nan train= 0.0000000 rnd 941: wh-err= 0.713957 th-err= 0.000000 test= nan train= 0.0000000 rnd 942: wh-err= 0.701771 th-err= 0.000000 test= nan train= 0.0000000 rnd 943: wh-err= 0.707734 th-err= 0.000000 test= nan train= 0.0000000 rnd 944: wh-err= 0.632169 th-err= 0.000000 test= nan train= 0.0000000 rnd 945: wh-err= 0.725756 th-err= 0.000000 test= nan train= 0.0000000 rnd 946: wh-err= 0.649142 th-err= 0.000000 test= nan train= 0.0000000 rnd 947: wh-err= 0.780384 th-err= 0.000000 test= nan train= 0.0000000 rnd 948: wh-err= 0.588386 th-err= 0.000000 test= nan train= 0.0000000 rnd 949: wh-err= 0.709961 th-err= 0.000000 test= nan train= 0.0000000 rnd 950: wh-err= 0.604565 th-err= 0.000000 test= nan train= 0.0000000 rnd 951: wh-err= 0.669109 th-err= 0.000000 test= nan train= 0.0000000 rnd 952: wh-err= 0.617456 th-err= 0.000000 test= nan train= 0.0000000 rnd 953: wh-err= 0.729033 th-err= 0.000000 test= nan train= 0.0000000 rnd 954: wh-err= 0.817293 th-err= 0.000000 test= nan train= 0.0000000 rnd 955: wh-err= 0.741523 th-err= 0.000000 test= nan train= 0.0000000 rnd 956: wh-err= 0.782246 th-err= 0.000000 test= nan train= 0.0000000 rnd 957: wh-err= 0.686186 th-err= 0.000000 test= nan train= 0.0000000 rnd 958: wh-err= 0.702295 th-err= 0.000000 test= nan train= 0.0000000 rnd 959: wh-err= 0.761110 th-err= 0.000000 test= nan train= 0.0000000 rnd 960: wh-err= 0.705389 th-err= 0.000000 test= nan train= 0.0000000 rnd 961: wh-err= 0.730807 th-err= 0.000000 test= nan train= 0.0000000 rnd 962: wh-err= 0.746296 th-err= 0.000000 test= nan train= 0.0000000 rnd 963: wh-err= 0.762304 th-err= 0.000000 test= nan train= 0.0000000 rnd 964: wh-err= 0.704765 th-err= 0.000000 test= nan train= 0.0000000 rnd 965: wh-err= 0.732909 th-err= 0.000000 test= nan train= 0.0000000 rnd 966: wh-err= 0.635711 th-err= 0.000000 test= nan train= 0.0000000 rnd 967: wh-err= 0.802806 th-err= 0.000000 test= nan train= 0.0000000 rnd 968: wh-err= 0.763108 th-err= 0.000000 test= nan train= 0.0000000 rnd 969: wh-err= 0.736854 th-err= 0.000000 test= nan train= 0.0000000 rnd 970: wh-err= 0.756431 th-err= 0.000000 test= nan train= 0.0000000 rnd 971: wh-err= 0.801918 th-err= 0.000000 test= nan train= 0.0000000 rnd 972: wh-err= 0.807889 th-err= 0.000000 test= nan train= 0.0000000 rnd 973: wh-err= 0.764983 th-err= 0.000000 test= nan train= 0.0000000 rnd 974: wh-err= 0.652312 th-err= 0.000000 test= nan train= 0.0000000 rnd 975: wh-err= 0.809554 th-err= 0.000000 test= nan train= 0.0000000 rnd 976: wh-err= 0.717694 th-err= 0.000000 test= nan train= 0.0000000 rnd 977: wh-err= 0.729677 th-err= 0.000000 test= nan train= 0.0000000 rnd 978: wh-err= 0.666379 th-err= 0.000000 test= nan train= 0.0000000 rnd 979: wh-err= 0.719767 th-err= 0.000000 test= nan train= 0.0000000 rnd 980: wh-err= 0.665133 th-err= 0.000000 test= nan train= 0.0000000 rnd 981: wh-err= 0.689841 th-err= 0.000000 test= nan train= 0.0000000 rnd 982: wh-err= 0.831636 th-err= 0.000000 test= nan train= 0.0000000 rnd 983: wh-err= 0.630858 th-err= 0.000000 test= nan train= 0.0000000 rnd 984: wh-err= 0.764778 th-err= 0.000000 test= nan train= 0.0000000 rnd 985: wh-err= 0.780228 th-err= 0.000000 test= nan train= 0.0000000 rnd 986: wh-err= 0.677934 th-err= 0.000000 test= nan train= 0.0000000 rnd 987: wh-err= 0.761755 th-err= 0.000000 test= nan train= 0.0000000 rnd 988: wh-err= 0.810521 th-err= 0.000000 test= nan train= 0.0000000 rnd 989: wh-err= 0.783799 th-err= 0.000000 test= nan train= 0.0000000 rnd 990: wh-err= 0.605316 th-err= 0.000000 test= nan train= 0.0000000 rnd 991: wh-err= 0.798086 th-err= 0.000000 test= nan train= 0.0000000 rnd 992: wh-err= 0.663295 th-err= 0.000000 test= nan train= 0.0000000 rnd 993: wh-err= 0.652560 th-err= 0.000000 test= nan train= 0.0000000 rnd 994: wh-err= 0.787398 th-err= 0.000000 test= nan train= 0.0000000 rnd 995: wh-err= 0.755397 th-err= 0.000000 test= nan train= 0.0000000 rnd 996: wh-err= 0.634022 th-err= 0.000000 test= nan train= 0.0000000 rnd 997: wh-err= 0.801760 th-err= 0.000000 test= nan train= 0.0000000 rnd 998: wh-err= 0.748409 th-err= 0.000000 test= nan train= 0.0000000 rnd 999: wh-err= 0.686591 th-err= 0.000000 test= nan train= 0.0000000 rnd 1000: wh-err= 0.715690 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 = 256.000000 / 256 = 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 [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 = 110.000000 / 110 = 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 0m5.044s user 0m2.032s sys 0m0.100s
Run specification 
Results
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