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OpenML
Task
Supervised Classification on cal_housing

Supervised Classification on cal_housing

Task 3687 Supervised Classification cal_housing 401 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_15 study_20 study_41 study_7 under100k under1m
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401 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8881, f_measure: 0.8391, kappa: 0.6654, kb_relative_information_score: 12546.9401, mean_absolute_error: 0.1906, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8391, predictive_accuracy: 0.8398, prior_entropy: 0.9745, recall: 0.8398, relative_absolute_error: 0.3952, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3524, root_relative_squared_error: 0.7175, scimark_benchmark: 1325.2092, usercpu_time_millis: 48940, usercpu_time_millis_testing: 48940,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8222, f_measure: 0.8159, kappa: 0.6261, kb_relative_information_score: 12572.3081, mean_absolute_error: 0.1857, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8267, predictive_accuracy: 0.8143, prior_entropy: 0.9745, recall: 0.8143, relative_absolute_error: 0.3848, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4309, root_relative_squared_error: 0.8773, scimark_benchmark: 889.3151, usercpu_time_millis: 1180, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7762, f_measure: 0.7987, kappa: 0.5794, kb_relative_information_score: 12233.3516, mean_absolute_error: 0.1935, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8175, predictive_accuracy: 0.8065, prior_entropy: 0.9745, recall: 0.8065, relative_absolute_error: 0.401, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4398, root_relative_squared_error: 0.8956, scimark_benchmark: 1315.395, usercpu_time_millis: 1161170, usercpu_time_millis_testing: 71500, usercpu_time_millis_training: 1089670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8286, f_measure: 0.8377, kappa: 0.6625, kb_relative_information_score: 13620.7575, mean_absolute_error: 0.1615, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8378, predictive_accuracy: 0.8385, prior_entropy: 0.9745, recall: 0.8385, relative_absolute_error: 0.3348, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4019, root_relative_squared_error: 0.8183, scimark_benchmark: 1250.8301, usercpu_time_millis: 3890, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 3860,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9176, f_measure: 0.8439, kappa: 0.6758, kb_relative_information_score: 11301.744, mean_absolute_error: 0.2298, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8438, predictive_accuracy: 0.8443, prior_entropy: 0.9745, recall: 0.8443, relative_absolute_error: 0.4764, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3334, root_relative_squared_error: 0.6788, scimark_benchmark: 1386.5717, usercpu_time_millis: 11730, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 11710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6615, f_measure: 0.657, kappa: 0.3105, kb_relative_information_score: 5603.6986, mean_absolute_error: 0.346, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.674, predictive_accuracy: 0.654, prior_entropy: 0.9745, recall: 0.654, relative_absolute_error: 0.7173, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.5882, root_relative_squared_error: 1.1977, scimark_benchmark: 942.6843, usercpu_time_millis: 3390, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 3370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9019, f_measure: 0.8223, kappa: 0.6319, kb_relative_information_score: 11362.1605, mean_absolute_error: 0.2231, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8225, predictive_accuracy: 0.8221, prior_entropy: 0.9745, recall: 0.8221, relative_absolute_error: 0.4624, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3538, root_relative_squared_error: 0.7204, scimark_benchmark: 1073.494, usercpu_time_millis: 140, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9196, f_measure: 0.8555, kappa: 0.6999, kb_relative_information_score: 12731.332, mean_absolute_error: 0.1921, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8554, predictive_accuracy: 0.8558, prior_entropy: 0.9745, recall: 0.8558, relative_absolute_error: 0.3982, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3303, root_relative_squared_error: 0.6725, scimark_benchmark: 1350.9691, usercpu_time_millis: 6240, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 6130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, f_measure: 0.8931, kappa: 0.7776, kb_relative_information_score: 13950.8146, mean_absolute_error: 0.1663, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8932, predictive_accuracy: 0.8935, prior_entropy: 0.9745, recall: 0.8935, relative_absolute_error: 0.3447, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.2768, root_relative_squared_error: 0.5637, scimark_benchmark: 1066.7184, usercpu_time_millis: 14460, usercpu_time_millis_testing: 2550, usercpu_time_millis_training: 11910,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8411, f_measure: 0.847, kappa: 0.6828, kb_relative_information_score: 13995.5045, mean_absolute_error: 0.1529, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.847, predictive_accuracy: 0.8471, prior_entropy: 0.9745, recall: 0.8471, relative_absolute_error: 0.317, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.391, root_relative_squared_error: 0.7962, scimark_benchmark: 1316.0472, usercpu_time_millis: 210, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9245, f_measure: 0.8694, kappa: 0.7288, kb_relative_information_score: 13510.1236, mean_absolute_error: 0.1746, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8693, predictive_accuracy: 0.8696, prior_entropy: 0.9745, recall: 0.8696, relative_absolute_error: 0.3619, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3186, root_relative_squared_error: 0.6486, scimark_benchmark: 1073.494, usercpu_time_millis: 300, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9205, f_measure: 0.8701, kappa: 0.7301, kb_relative_information_score: 13239.1926, mean_absolute_error: 0.1837, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.87, predictive_accuracy: 0.8704, prior_entropy: 0.9745, recall: 0.8704, relative_absolute_error: 0.3809, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3215, root_relative_squared_error: 0.6546, scimark_benchmark: 1336.3256, usercpu_time_millis: 3970, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 3960,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6019, f_measure: 0.6221, kappa: 0.2099, kb_relative_information_score: 4555.2492, mean_absolute_error: 0.3702, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.6214, predictive_accuracy: 0.6298, prior_entropy: 0.9745, recall: 0.6298, relative_absolute_error: 0.7673, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.6084, root_relative_squared_error: 1.2388, scimark_benchmark: 1308.9788, usercpu_time_millis: 25130, usercpu_time_millis_testing: 3910, usercpu_time_millis_training: 21220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9319, f_measure: 0.8552, kappa: 0.6986, kb_relative_information_score: 13137.0394, mean_absolute_error: 0.1805, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8556, predictive_accuracy: 0.8561, prior_entropy: 0.9745, recall: 0.8561, relative_absolute_error: 0.3741, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3154, root_relative_squared_error: 0.6423, scimark_benchmark: 1358.4523, usercpu_time_millis: 2180, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 2140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7243, f_measure: 0.7426, kappa: 0.4618, kb_relative_information_score: 9679.5983, mean_absolute_error: 0.2522, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.746, predictive_accuracy: 0.7478, prior_entropy: 0.9745, recall: 0.7478, relative_absolute_error: 0.5228, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.5022, root_relative_squared_error: 1.0226, scimark_benchmark: 1351.788, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8363, f_measure: 0.838, kappa: 0.666, kb_relative_information_score: 13570.2298, mean_absolute_error: 0.1627, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8397, predictive_accuracy: 0.8373, prior_entropy: 0.9745, recall: 0.8373, relative_absolute_error: 0.3372, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4034, root_relative_squared_error: 0.8213, scimark_benchmark: 1353.5686, usercpu_time_millis: 5220, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 5180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4997, f_measure: 0.4424, kb_relative_information_score: -0.0718, mean_absolute_error: 0.4824, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.3525, predictive_accuracy: 0.5938, prior_entropy: 0.9745, recall: 0.5938, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4911, root_relative_squared_error: 1, scimark_benchmark: 1358.4955, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9069, f_measure: 0.8718, kappa: 0.7339, kb_relative_information_score: 13881.9158, mean_absolute_error: 0.1646, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8717, predictive_accuracy: 0.8719, prior_entropy: 0.9745, recall: 0.8719, relative_absolute_error: 0.3412, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3236, root_relative_squared_error: 0.6589, scimark_benchmark: 1605.6303, usercpu_time_millis: 630, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 610,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8211, f_measure: 0.751, kappa: 0.48, kb_relative_information_score: 10177.6875, mean_absolute_error: 0.2417, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.7685, predictive_accuracy: 0.7616, prior_entropy: 0.9745, recall: 0.7616, relative_absolute_error: 0.501, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4435, root_relative_squared_error: 0.9031, scimark_benchmark: 931.2336, usercpu_time_millis: 2020, usercpu_time_millis_testing: 570, usercpu_time_millis_training: 1450,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8438, f_measure: 0.7545, kappa: 0.4874, kb_relative_information_score: 10460.8858, mean_absolute_error: 0.2344, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.7713, predictive_accuracy: 0.7646, prior_entropy: 0.9745, recall: 0.7646, relative_absolute_error: 0.4859, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4452, root_relative_squared_error: 0.9065, scimark_benchmark: 945.6434, usercpu_time_millis: 4270, usercpu_time_millis_testing: 1130, usercpu_time_millis_training: 3140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8631, f_measure: 0.7805, kappa: 0.541, kb_relative_information_score: 11186.2002, mean_absolute_error: 0.2189, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.789, predictive_accuracy: 0.7864, prior_entropy: 0.9745, recall: 0.7864, relative_absolute_error: 0.4538, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.42, root_relative_squared_error: 0.8552, scimark_benchmark: 941.7954, usercpu_time_millis: 2800, usercpu_time_millis_testing: 690, usercpu_time_millis_training: 2110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8713, f_measure: 0.8052, kappa: 0.5935, kb_relative_information_score: 10958.5409, mean_absolute_error: 0.2307, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8063, predictive_accuracy: 0.8072, prior_entropy: 0.9745, recall: 0.8072, relative_absolute_error: 0.4782, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3779, root_relative_squared_error: 0.7694, scimark_benchmark: 923.7642, usercpu_time_millis: 2720, usercpu_time_millis_testing: 680, usercpu_time_millis_training: 2040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8843, f_measure: 0.8058, kappa: 0.595, kb_relative_information_score: 10270.1726, mean_absolute_error: 0.2509, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8065, predictive_accuracy: 0.8076, prior_entropy: 0.9745, recall: 0.8076, relative_absolute_error: 0.5201, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3663, root_relative_squared_error: 0.7457, scimark_benchmark: 894.7455, usercpu_time_millis: 2770, usercpu_time_millis_testing: 680, usercpu_time_millis_training: 2090,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9037, f_measure: 0.8085, kappa: 0.5997, kb_relative_information_score: 12416.143, mean_absolute_error: 0.1901, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8137, predictive_accuracy: 0.8122, prior_entropy: 0.9745, recall: 0.8122, relative_absolute_error: 0.394, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.394, root_relative_squared_error: 0.8023, scimark_benchmark: 936.6206, usercpu_time_millis: 10130, usercpu_time_millis_testing: 200, usercpu_time_millis_training: 9930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8939, f_measure: 0.7979, kappa: 0.5775, kb_relative_information_score: 12020.2638, mean_absolute_error: 0.1992, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8035, predictive_accuracy: 0.8021, prior_entropy: 0.9745, recall: 0.8021, relative_absolute_error: 0.4129, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4054, root_relative_squared_error: 0.8254, scimark_benchmark: 936.6206, usercpu_time_millis: 5330, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 5250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8827, f_measure: 0.7822, kappa: 0.5446, kb_relative_information_score: 11416.9866, mean_absolute_error: 0.2127, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.7888, predictive_accuracy: 0.7874, prior_entropy: 0.9745, recall: 0.7874, relative_absolute_error: 0.4409, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4233, root_relative_squared_error: 0.862, scimark_benchmark: 942.1229, usercpu_time_millis: 2190, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 2150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8536, f_measure: 0.7716, kappa: 0.5224, kb_relative_information_score: 10913.7392, mean_absolute_error: 0.2241, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.7776, predictive_accuracy: 0.7769, prior_entropy: 0.9745, recall: 0.7769, relative_absolute_error: 0.4646, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.4417, root_relative_squared_error: 0.8993, scimark_benchmark: 922.9039, usercpu_time_millis: 1100, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 1070,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8287, f_measure: 0.7608, kappa: 0.4999, kb_relative_information_score: 10134.6545, mean_absolute_error: 0.2437, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.7645, predictive_accuracy: 0.7655, prior_entropy: 0.9745, recall: 0.7655, relative_absolute_error: 0.5052, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.455, root_relative_squared_error: 0.9264, scimark_benchmark: 938.9865, usercpu_time_millis: 600, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9451, f_measure: 0.8755, kappa: 0.741, kb_relative_information_score: 13000.4587, mean_absolute_error: 0.1893, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8757, predictive_accuracy: 0.8761, prior_entropy: 0.9745, recall: 0.8761, relative_absolute_error: 0.3924, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.2999, root_relative_squared_error: 0.6105, scimark_benchmark: 936.6206, usercpu_time_millis: 6840, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 6820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9369, f_measure: 0.865, kappa: 0.7189, kb_relative_information_score: 12367.2829, mean_absolute_error: 0.2049, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8655, predictive_accuracy: 0.8658, prior_entropy: 0.9745, recall: 0.8658, relative_absolute_error: 0.4246, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.3113, root_relative_squared_error: 0.6339, scimark_benchmark: 924.6116, usercpu_time_millis: 4620, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 4600,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9622, build_cpu_time: 59.3526, build_memory: 1992695326.4, f_measure: 0.8973, kappa: 0.7866, kb_relative_information_score: 14353.6252, mean_absolute_error: 0.156, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8972, predictive_accuracy: 0.8975, prior_entropy: 0.9745, recall: 0.8975, relative_absolute_error: 0.3234, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.2724, root_relative_squared_error: 0.5547, scimark_benchmark: 929.779,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9614, build_cpu_time: 37.1061, build_memory: 1395774992.8, f_measure: 0.8961, kappa: 0.7841, kb_relative_information_score: 14333.8265, mean_absolute_error: 0.1563, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8961, predictive_accuracy: 0.8963, prior_entropy: 0.9745, recall: 0.8963, relative_absolute_error: 0.3239, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.2738, root_relative_squared_error: 0.5575, scimark_benchmark: 878.6719,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9592, build_cpu_time: 15.4373, build_memory: 1632703482.4, f_measure: 0.8938, kappa: 0.7794, kb_relative_information_score: 14294.9002, mean_absolute_error: 0.1568, mean_prior_absolute_error: 0.4824, number_of_instances: 20640, precision: 0.8937, predictive_accuracy: 0.894, prior_entropy: 0.9745, recall: 0.894, relative_absolute_error: 0.325, root_mean_prior_squared_error: 0.4911, root_mean_squared_error: 0.2771, root_relative_squared_error: 0.5642, scimark_benchmark: 909.8478,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs