Tabular Datasets

Benchmarks

Task Name	Dataset Name	SOTA Result
Tabular Regression	52 Tabular Datasets (test)	NMAE0.139	85
Simulatability	Tabular Datasets Aggregate (test)	Accuracy (w/o explanation)74.63	18
Tabular Classification	10 Tabular Datasets Missing rate > 10% MNAR (cross-method intersection)	AUC81.72	15
Anomaly Detection	34 Tabular Datasets average (test)	AUC-PR (Baseline)0.729	14
Synthetic Tabular Data Generation Evaluation	11 Tabular Datasets Average (test)	RMSE0.086	10
Synthetic Tabular Data Generation	11 Tabular Datasets Average Rank (test)	RMSE2.6	10
Association Rule Mining	Larger Tabular Datasets	Accuracy88.13	9
Association Rule Mining	Tabular Datasets Small	Accuracy84.47	9
Tabular Classification	18 Tabular Datasets (kr-vs-kp, mfeat-factors, credit-g, vehicle, kc1, bank-marketing, blood-transfusion, cnae-9, nomao, phoneme, adult, segment, christine, jasmine, sylvine, riccardo, dilbert, fabert)	Test Statistic124.5	7
Association Rule Learning	5 Small Tabular Datasets Average	Number of Rules1,462	7
Tabular Classification	19 Tabular Datasets Aggregate	Normalized Mean77.6	4
Multi-class Classification	33 Tabular Datasets Multi-class	Accuracy94.82	4
Binary Classification	33 tabular datasets Binary	Accuracy88.9	4

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