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tabular-benchmark
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clf_cat_albert
·
58.3k rows
clf_cat_albert (58.3k rows)
clf_cat_compas-two-years (4.97k rows)
clf_cat_covertype (424k rows)
clf_cat_default-of-credit-card-clients (13.3k rows)
clf_cat_electricity (38.5k rows)
clf_cat_eye_movements (7.61k rows)
clf_cat_road-safety (112k rows)
clf_num_Bioresponse (3.43k rows)
clf_num_Diabetes130US (71.1k rows)
clf_num_Higgs (940k rows)
clf_num_MagicTelescope (13.4k rows)
clf_num_MiniBooNE (73k rows)
clf_num_bank-marketing (10.6k rows)
clf_num_california (20.6k rows)
clf_num_covertype (567k rows)
clf_num_credit (16.7k rows)
clf_num_default-of-credit-card-clients (13.3k rows)
clf_num_electricity (38.5k rows)
clf_num_eye_movements (7.61k rows)
clf_num_heloc (10k rows)
clf_num_house_16H (13.5k rows)
clf_num_jannis (57.6k rows)
clf_num_pol (10.1k rows)
reg_cat_Airlines_DepDelay_1M (1M rows)
reg_cat_Allstate_Claims_Severity (188k rows)
reg_cat_Bike_Sharing_Demand (17.4k rows)
reg_cat_Brazilian_houses (10.7k rows)
reg_cat_Mercedes_Benz_Greener_Manufacturing (4.21k rows)
reg_cat_SGEMM_GPU_kernel_performance (242k rows)
reg_cat_abalone (4.18k rows)
reg_cat_analcatdata_supreme (4.05k rows)
reg_cat_delays_zurich_transport (5.47M rows)
reg_cat_diamonds (53.9k rows)
reg_cat_house_sales (21.6k rows)
reg_cat_medical_charges (163k rows)
reg_cat_nyc-taxi-green-dec-2016 (582k rows)
reg_cat_particulate-matter-ukair-2017 (394k rows)
reg_cat_seattlecrime6 (52k rows)
reg_cat_topo_2_1 (8.89k rows)
reg_cat_visualizing_soil (8.64k rows)
reg_num_Ailerons (13.8k rows)
reg_num_Bike_Sharing_Demand (17.4k rows)
reg_num_Brazilian_houses (10.7k rows)
reg_num_MiamiHousing2016 (13.9k rows)
reg_num_abalone (4.18k rows)
reg_num_cpu_act (8.19k rows)
reg_num_delays_zurich_transport (5.47M rows)
reg_num_diamonds (53.9k rows)
reg_num_elevators (16.6k rows)
reg_num_house_16H (22.8k rows)
reg_num_house_sales (21.6k rows)
reg_num_houses (20.6k rows)
reg_num_medical_charges (163k rows)
reg_num_nyc-taxi-green-dec-2016 (582k rows)
reg_num_pol (15k rows)
reg_num_sulfur (10.1k rows)
reg_num_superconduct (21.3k rows)
reg_num_wine_quality (6.5k rows)
reg_num_yprop_4_1 (8.89k rows)
Split (1)
train
·
58.3k rows
train (58.3k rows)
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