Pipeline
Compete Name:tabular-resnet
Pipeline Name:
Experimental Results
| Pipeline ID | Execution time | Memory | Score | Library & Version |
|---|---|---|---|---|
| 36157 | 2897.2932522 | 1886.0163888931 | 0.925125 | pandas,1.2.4 |
| 36157 | 2897.2932522 | 1886.0163888931 | 0.925125 | scikit-learn,1.0.1 |
| 36157 | 3326.8914602 | 1888.8116064072 | 0.931575 | pandas,1.2.4 |
| 36157 | 3326.8914602 | 1888.8116064072 | 0.931575 | scikit-learn,0.24.2 |
| 36157 | 3104.4978158999998 | 1888.6725273132 | 0.927625 | pandas,1.2.4 |
| 36157 | 3104.4978158999998 | 1888.6725273132 | 0.927625 | scikit-learn,0.23.2 |
| 36157 | 2968.3163010000003 | 1885.0313100815 | 0.93145 | pandas,1.2.4 |
| 36157 | 2968.3163010000003 | 1885.0313100815 | 0.93145 | scikit-learn,0.22.1 |
| 36157 | 2943.8342973999997 | 1885.0255994797 | 0.930175 | pandas,1.2.4 |
| 36157 | 2943.8342973999997 | 1885.0255994797 | 0.930175 | scikit-learn,0.22 |
| 36157 | 3301.8422067 | 1885.5834674835 | 0.9375 | pandas,1.2.4 |
| 36157 | 3301.8422067 | 1885.5834674835 | 0.9375 | scikit-learn,0.21.3 |
| 36157 | 3051.4845741999998 | 1886.5448360443 | 0.939175 | pandas,1.2.4 |
| 36157 | 3051.4845741999998 | 1886.5448360443 | 0.939175 | scikit-learn,0.20.3 |
| 36157 | 3215.6369555 | 1885.2800683975 | 0.933625 | pandas,1.2.4 |
| 36157 | 3215.6369555 | 1885.2800683975 | 0.933625 | scikit-learn,0.19.2 |
| 36157 | 3114.3002286 | 1885.3649597168 | 0.931775 | pandas,1.1.5 |
| 36157 | 3114.3002286 | 1885.3649597168 | 0.931775 | scikit-learn,1.0.1 |
| 36157 | 3202.9493018000003 | 1888.1818284988 | 0.931975 | pandas,1.1.5 |
| 36157 | 3202.9493018000003 | 1888.1818284988 | 0.931975 | scikit-learn,0.24.2 |
| 36157 | 2909.0879789 | 1888.0375108719 | 0.9283 | pandas,1.1.5 |
| 36157 | 2909.0879789 | 1888.0375108719 | 0.9283 | scikit-learn,0.23.2 |
| 36157 | 3237.8999537 | 1884.3925514221 | 0.933775 | pandas,1.1.5 |
| 36157 | 3237.8999537 | 1884.3925514221 | 0.933775 | scikit-learn,0.22.1 |
| 36157 | 3041.467297 | 1884.4970331192 | 0.93125 | pandas,1.1.5 |
| 36157 | 3041.467297 | 1884.4970331192 | 0.93125 | scikit-learn,0.22 |
| 36157 | 3267.6088558 | 1884.9428672791 | 0.92955 | pandas,1.1.5 |
| 36157 | 3267.6088558 | 1884.9428672791 | 0.92955 | scikit-learn,0.21.3 |
| 36157 | 3271.9003068 | 1885.913061142 | 0.941825 | pandas,1.1.5 |
| 36157 | 3271.9003068 | 1885.913061142 | 0.941825 | scikit-learn,0.20.3 |
| 36157 | 3012.1628348 | 1884.6426725388 | 0.9379 | pandas,1.1.5 |
| 36157 | 3012.1628348 | 1884.6426725388 | 0.9379 | scikit-learn,0.19.2 |
| 36157 | 3055.5986517 | 1884.8961906433 | 0.933225 | pandas,1.0.5 |
| 36157 | 3055.5986517 | 1884.8961906433 | 0.933225 | scikit-learn,1.0.1 |
| 36157 | 3130.111177 | 1887.5879087448 | 0.930675 | pandas,1.0.5 |
| 36157 | 3130.111177 | 1887.5879087448 | 0.930675 | scikit-learn,0.24.2 |
| 36157 | 2610.6087032 | 1887.4459543228 | 0.925425 | pandas,1.0.5 |
| 36157 | 2610.6087032 | 1887.4459543228 | 0.925425 | scikit-learn,0.23.2 |
| 36157 | 2840.1927584 | 1883.7942905426 | 0.9339 | pandas,1.0.5 |
| 36157 | 2840.1927584 | 1883.7942905426 | 0.9339 | scikit-learn,0.22.1 |
| 36157 | 2795.8129852 | 1883.7886505127 | 0.929675 | pandas,1.0.5 |
| 36157 | 2795.8129852 | 1883.7886505127 | 0.929675 | scikit-learn,0.22 |
| 36157 | 3401.9343166000003 | 1884.350063324 | 0.9394 | pandas,1.0.5 |
| 36157 | 3401.9343166000003 | 1884.350063324 | 0.9394 | scikit-learn,0.21.3 |
| 36157 | 3233.3799752 | 1885.3159542084 | 0.941325 | pandas,1.0.5 |
| 36157 | 3233.3799752 | 1885.3159542084 | 0.941325 | scikit-learn,0.20.3 |
| 36157 | 3019.5464938 | 1884.0549631119 | 0.93665 | pandas,1.0.5 |
| 36157 | 3019.5464938 | 1884.0549631119 | 0.93665 | scikit-learn,0.19.2 |
| 36157 | 2841.0097584 | 1884.6644659042 | 0.93195 | pandas,0.25.3 |
| 36157 | 2841.0097584 | 1884.6644659042 | 0.93195 | scikit-learn,1.0.1 |
| 36157 | 2931.1574027 | 1887.4747390747 | 0.93145 | pandas,0.25.3 |
| 36157 | 2931.1574027 | 1887.4747390747 | 0.93145 | scikit-learn,0.24.2 |
| 36157 | 3145.6569725 | 1887.3348731995 | 0.93345 | pandas,0.25.3 |
| 36157 | 3145.6569725 | 1887.3348731995 | 0.93345 | scikit-learn,0.23.2 |
| 36157 | 3136.3903031 | 1883.6680603027 | 0.931925 | pandas,0.25.3 |
| 36157 | 3136.3903031 | 1883.6680603027 | 0.931925 | scikit-learn,0.22.1 |
| 36157 | 2776.2596862 | 1883.665137291 | 0.927025 | pandas,0.25.3 |
| 36157 | 2776.2596862 | 1883.665137291 | 0.927025 | scikit-learn,0.22 |
| 36157 | 3044.0438373 | 1884.2252235413 | 0.9372 | pandas,0.25.3 |
| 36157 | 3044.0438373 | 1884.2252235413 | 0.9372 | scikit-learn,0.21.3 |
| 36157 | 3107.7584723 | 1885.1935100555 | 0.93865 | pandas,0.25.3 |
| 36157 | 3107.7584723 | 1885.1935100555 | 0.93865 | scikit-learn,0.20.3 |
| 36157 | 3274.3635901 | 1883.9388237 | 0.941125 | pandas,0.25.3 |
| 36157 | 3274.3635901 | 1883.9388237 | 0.941125 | scikit-learn,0.19.2 |
| 36157 | 3257.9472556 | 1884.794793129 | 0.933725 | pandas,0.24.2 |
| 36157 | 3257.9472556 | 1884.794793129 | 0.933725 | scikit-learn,1.0.1 |
| 36157 | 3032.1136844000002 | 1887.6026697159 | 0.931125 | pandas,0.24.2 |
| 36157 | 3032.1136844000002 | 1887.6026697159 | 0.931125 | scikit-learn,0.24.2 |
| 36157 | 2852.7626238999997 | 1887.4634332657 | 0.92835 | pandas,0.24.2 |
| 36157 | 2852.7626238999997 | 1887.4634332657 | 0.92835 | scikit-learn,0.23.2 |
| 36157 | 2901.1054308 | 1883.8046970367 | 0.931275 | pandas,0.24.2 |
| 36157 | 2901.1054308 | 1883.8046970367 | 0.931275 | scikit-learn,0.22.1 |
| 36157 | 2907.0983488 | 1883.8003873825 | 0.935825 | pandas,0.24.2 |
| 36157 | 2907.0983488 | 1883.8003873825 | 0.935825 | scikit-learn,0.22 |
| 36157 | 3324.0223688 | 1884.356054306 | 0.934325 | pandas,0.24.2 |
| 36157 | 3324.0223688 | 1884.356054306 | 0.934325 | scikit-learn,0.21.3 |
| 36157 | 3062.6648575 | 1885.3201751709 | 0.934075 | pandas,0.24.2 |
| 36157 | 3062.6648575 | 1885.3201751709 | 0.934075 | scikit-learn,0.20.3 |
| 36157 | 2989.6458749000003 | 1884.0659723282 | 0.9389 | pandas,0.24.2 |
| 36157 | 2989.6458749000003 | 1884.0659723282 | 0.9389 | scikit-learn,0.19.2 |
| 36157 | 3197.4800371 | 1883.657989502 | 0.9398 | pandas,0.23.4 |
| 36157 | 3197.4800371 | 1883.657989502 | 0.9398 | scikit-learn,1.0.1 |
| 36157 | 3382.4384259999997 | 1886.5436115265 | 0.93555 | pandas,0.23.4 |
| 36157 | 3382.4384259999997 | 1886.5436115265 | 0.93555 | scikit-learn,0.24.2 |
| 36157 | 3359.3933801 | 1886.3230361938 | 0.9347 | pandas,0.23.4 |
| 36157 | 3359.3933801 | 1886.3230361938 | 0.9347 | scikit-learn,0.23.2 |
| 36157 | 2814.3954641 | 1882.6684246063 | 0.928825 | pandas,0.23.4 |
| 36157 | 2814.3954641 | 1882.6684246063 | 0.928825 | scikit-learn,0.22.1 |
| 36157 | 3185.6358906 | 1882.6618041992 | 0.935175 | pandas,0.23.4 |
| 36157 | 3185.6358906 | 1882.6618041992 | 0.935175 | scikit-learn,0.22 |
| 36157 | 3487.2864506 | 1883.2220172882 | 0.93735 | pandas,0.23.4 |
| 36157 | 3487.2864506 | 1883.2220172882 | 0.93735 | scikit-learn,0.21.3 |
| 36157 | 3017.5503743000004 | 1884.2936916351 | 0.936875 | pandas,0.23.4 |
| 36157 | 3017.5503743000004 | 1884.2936916351 | 0.936875 | scikit-learn,0.20.3 |
| 36157 | 3326.7739189 | 1882.9262132645 | 0.937075 | pandas,0.23.4 |
| 36157 | 3326.7739189 | 1882.9262132645 | 0.937075 | scikit-learn,0.19.2 |
