Pipeline
Compete Name:tps-aug-2021-eda-rf
Pipeline Name:
Experimental Results
Pipeline ID | Execution time | Memory | Score | Library & Version |
---|---|---|---|---|
33342 | 2535.9552935 | 1037.0310192108 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2535.9552935 | 1037.0310192108 | 7.912873919301641 | scikit-learn,1.0.1 |
33342 | 2532.2823538 | 1039.437921524 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2532.2823538 | 1039.437921524 | 7.912873919301641 | scikit-learn,0.24.2 |
33342 | 2540.911312 | 1039.2379627228 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2540.911312 | 1039.2379627228 | 7.912873919301641 | scikit-learn,0.23.2 |
33342 | 2557.248867 | 1035.620672226 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2557.248867 | 1035.620672226 | 7.912873919301641 | scikit-learn,0.22.1 |
33342 | 2486.7332373 | 1035.6041326523 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2486.7332373 | 1035.6041326523 | 7.912873919301641 | scikit-learn,0.22 |
33342 | 2524.8036763 | 1035.8664579391 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2524.8036763 | 1035.8664579391 | 7.912873919301641 | scikit-learn,0.21.3 |
33342 | 2511.4194907 | 1033.991768837 | 7.912873919301641 | numpy,1.17.4 |
33342 | 2511.4194907 | 1033.991768837 | 7.912873919301641 | scikit-learn,0.20.3 |
33342 | 2557.7240482 | 1032.4467201233 | 7.912873999424376 | numpy,1.17.4 |
33342 | 2557.7240482 | 1032.4467201233 | 7.912873999424376 | scikit-learn,0.19.2 |
33342 | 2610.1430595 | 1037.9499969482 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2610.1430595 | 1037.9499969482 | 7.912873919301641 | scikit-learn,1.0.1 |
33342 | 2534.5453716 | 1040.3403873444 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2534.5453716 | 1040.3403873444 | 7.912873919301641 | scikit-learn,0.24.2 |
33342 | 2539.1864743 | 1040.1418371201 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2539.1864743 | 1040.1418371201 | 7.912873919301641 | scikit-learn,0.23.2 |
33342 | 2557.1437936999996 | 1036.493393898 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2557.1437936999996 | 1036.493393898 | 7.912873919301641 | scikit-learn,0.22.1 |
33342 | 2475.3331684 | 1036.4761323929 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2475.3331684 | 1036.4761323929 | 7.912873919301641 | scikit-learn,0.22 |
33342 | 2522.3639952 | 1036.8164920807 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2522.3639952 | 1036.8164920807 | 7.912873919301641 | scikit-learn,0.21.3 |
33342 | 2564.8786883 | 1034.8941869736 | 7.912873919301641 | numpy,1.18.5 |
33342 | 2564.8786883 | 1034.8941869736 | 7.912873919301641 | scikit-learn,0.20.3 |
33342 | 2570.2963317000003 | 1033.3492460251 | 7.912873999424376 | numpy,1.18.5 |
33342 | 2570.2963317000003 | 1033.3492460251 | 7.912873999424376 | scikit-learn,0.19.2 |
33342 | 2533.3847757999997 | 1038.0706501007 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2533.3847757999997 | 1038.0706501007 | 7.912873919301641 | scikit-learn,1.0.1 |
33342 | 2532.2484187 | 1040.4591188431 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2532.2484187 | 1040.4591188431 | 7.912873919301641 | scikit-learn,0.24.2 |
33342 | 2620.0850709 | 1040.2609205246 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2620.0850709 | 1040.2609205246 | 7.912873919301641 | scikit-learn,0.23.2 |
33342 | 2476.8141858999998 | 1036.614481926 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2476.8141858999998 | 1036.614481926 | 7.912873919301641 | scikit-learn,0.22.1 |
33342 | 2556.9823501 | 1036.5961074829 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2556.9823501 | 1036.5961074829 | 7.912873919301641 | scikit-learn,0.22 |
33342 | 2599.4152464999997 | 1036.9365978241 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2599.4152464999997 | 1036.9365978241 | 7.912873919301641 | scikit-learn,0.21.3 |
33342 | 2565.2849494 | 1035.0112886429 | 7.912873919301641 | numpy,1.19.5 |
33342 | 2565.2849494 | 1035.0112886429 | 7.912873919301641 | scikit-learn,0.20.3 |
33342 | 2613.9177154 | 1033.4656467438 | 7.912873999424376 | numpy,1.19.5 |
33342 | 2613.9177154 | 1033.4656467438 | 7.912873999424376 | scikit-learn,0.19.2 |