31753

Pipeline

Compete Name:tabular-playground-series-solution

Pipeline Name:

Experimental Results

Pipeline ID	Execution time	Memory	Score	Library & Version
31753	49.7858751	73.0153827667	0.02665214501114367	numpy,1.17.4
31753	49.7858751	73.0153827667	0.02665214501114367	scikit-learn,1.0.1
31753	50.134166500000006	75.453997612	0.02665214501114367	numpy,1.17.4
31753	50.134166500000006	75.453997612	0.02665214501114367	scikit-learn,0.24.2
31753	36.064617	75.2523708344	0.02665214501114367	numpy,1.17.4
31753	36.064617	75.2523708344	0.02665214501114367	scikit-learn,0.23.2
31753	35.820448500000005	71.661231041	0.026622314501977357	numpy,1.17.4
31753	35.820448500000005	71.661231041	0.026622314501977357	scikit-learn,0.22.1
31753	35.787378000000004	71.6445856094	0.026622314501977357	numpy,1.17.4
31753	35.787378000000004	71.6445856094	0.026622314501977357	scikit-learn,0.22
31753	48.8964697	72.0034217834	0.03214475169784462	numpy,1.17.4
31753	48.8964697	72.0034217834	0.03214475169784462	scikit-learn,0.21.3
31753	48.5786506	71.4513101578	0.03214475169784462	numpy,1.17.4
31753	48.5786506	71.4513101578	0.03214475169784462	scikit-learn,0.20.3
31753	48.5910697	69.8218927383	0.03214475169784462	numpy,1.17.4
31753	48.5910697	69.8218927383	0.03214475169784462	scikit-learn,0.19.2
31753	49.7083781	73.9165678024	0.02665214501114367	numpy,1.18.5
31753	49.7083781	73.9165678024	0.02665214501114367	scikit-learn,1.0.1
31753	50.8286736	76.3586139679	0.02665214501114367	numpy,1.18.5
31753	50.8286736	76.3586139679	0.02665214501114367	scikit-learn,0.24.2
31753	35.9574484	76.1583404541	0.02665214501114367	numpy,1.18.5
31753	35.9574484	76.1583404541	0.02665214501114367	scikit-learn,0.23.2
31753	35.8077562	72.5667457581	0.026622314501977357	numpy,1.18.5
31753	35.8077562	72.5667457581	0.026622314501977357	scikit-learn,0.22.1
31753	35.968304700000004	72.5505828857	0.026622314501977357	numpy,1.18.5
31753	35.968304700000004	72.5505828857	0.026622314501977357	scikit-learn,0.22
31753	49.027193600000004	72.9085712433	0.03214475169784462	numpy,1.18.5
31753	49.027193600000004	72.9085712433	0.03214475169784462	scikit-learn,0.21.3
31753	48.460203	72.3574857712	0.03214475169784462	numpy,1.18.5
31753	48.460203	72.3574857712	0.03214475169784462	scikit-learn,0.20.3
31753	48.3647891	70.7277336121	0.03214475169784462	numpy,1.18.5
31753	48.3647891	70.7277336121	0.03214475169784462	scikit-learn,0.19.2
31753	49.4765617	74.0295934677	0.02665214501114367	numpy,1.19.5
31753	49.4765617	74.0295934677	0.02665214501114367	scikit-learn,1.0.1
31753	49.3975715	76.4690504074	0.02665214501114367	numpy,1.19.5
31753	49.3975715	76.4690504074	0.02665214501114367	scikit-learn,0.24.2
31753	35.6629954	76.2680644989	0.02665214501114367	numpy,1.19.5
31753	35.6629954	76.2680644989	0.02665214501114367	scikit-learn,0.23.2
31753	35.4878012	72.6769695282	0.026622314501977357	numpy,1.19.5
31753	35.4878012	72.6769695282	0.026622314501977357	scikit-learn,0.22.1
31753	35.4188538	72.6600351334	0.026622314501977357	numpy,1.19.5
31753	35.4188538	72.6600351334	0.026622314501977357	scikit-learn,0.22
31753	26.002500100000002	73.0165452957	0.03214475169784462	numpy,1.19.5
31753	26.002500100000002	73.0165452957	0.03214475169784462	scikit-learn,0.21.3
31753	26.1992337	72.4656257629	0.03214475169784462	numpy,1.19.5
31753	26.1992337	72.4656257629	0.03214475169784462	scikit-learn,0.20.3
31753	26.0773567	70.835401535	0.03214475169784462	numpy,1.19.5
31753	26.0773567	70.835401535	0.03214475169784462	scikit-learn,0.19.2

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