OpenML
Supervised Classification on colic

Supervised Classification on colic

Task 27 Supervised Classification colic 754 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8683, f_measure: 0.8223, kappa: 0.6169, kb_relative_information_score: 192.781, mean_absolute_error: 0.2272, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8234, prior_entropy: 0.9509, recall: 0.8234, relative_absolute_error: 0.4873, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3679, root_relative_squared_error: 0.7623, scimark_benchmark: 1310.3951, usercpu_time_millis: 2550, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 2500,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8688, f_measure: 0.837, kappa: 0.6501, kb_relative_information_score: 208.2546, mean_absolute_error: 0.2043, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.837, predictive_accuracy: 0.837, prior_entropy: 0.9509, recall: 0.837, relative_absolute_error: 0.4383, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.366, root_relative_squared_error: 0.7582, scimark_benchmark: 1346.9602, usercpu_time_millis: 1150, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9049, f_measure: 0.8537, kappa: 0.6827, kb_relative_information_score: 172.4716, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8555, predictive_accuracy: 0.856, prior_entropy: 0.9509, recall: 0.856, relative_absolute_error: 0.5721, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3379, root_relative_squared_error: 0.7, scimark_benchmark: 1325.942, usercpu_time_millis: 560, usercpu_time_millis_testing: 180, usercpu_time_millis_training: 380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8304, f_measure: 0.7866, kappa: 0.5395, kb_relative_information_score: 166.5146, mean_absolute_error: 0.258, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.786, predictive_accuracy: 0.788, prior_entropy: 0.9509, recall: 0.788, relative_absolute_error: 0.5534, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4032, root_relative_squared_error: 0.8353, scimark_benchmark: 1313.5726, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8288, f_measure: 0.8372, kappa: 0.6468, kb_relative_information_score: 190.4372, mean_absolute_error: 0.2373, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8386, predictive_accuracy: 0.8397, prior_entropy: 0.9509, recall: 0.8397, relative_absolute_error: 0.5091, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3668, root_relative_squared_error: 0.7599, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8209, f_measure: 0.8557, kappa: 0.6863, kb_relative_information_score: 197.5333, mean_absolute_error: 0.2331, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8595, predictive_accuracy: 0.8587, prior_entropy: 0.9509, recall: 0.8587, relative_absolute_error: 0.5001, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.343, root_relative_squared_error: 0.7106, scimark_benchmark: 1066.7184, usercpu_time_millis: 180, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7798, f_measure: 0.8078, kappa: 0.5817, kb_relative_information_score: 215.3662, mean_absolute_error: 0.1875, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8115, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.4022, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.433, root_relative_squared_error: 0.8971, scimark_benchmark: 1325.2092, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4592, f_measure: 0.502, kappa: -0.0875, kb_relative_information_score: -16.5846, mean_absolute_error: 0.4728, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.4899, predictive_accuracy: 0.5272, prior_entropy: 0.9509, recall: 0.5272, relative_absolute_error: 1.0143, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.6876, root_relative_squared_error: 1.4246, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, f_measure: 0.8316, kappa: 0.6348, kb_relative_information_score: 186.0312, mean_absolute_error: 0.2424, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8329, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.5199, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.7507, scimark_benchmark: 1466.6185, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8139, f_measure: 0.8171, kappa: 0.6129, kb_relative_information_score: 217.5752, mean_absolute_error: 0.1848, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.3964, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4299, root_relative_squared_error: 0.8906, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8146, f_measure: 0.8204, kappa: 0.6139, kb_relative_information_score: 221.7893, mean_absolute_error: 0.18, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8201, predictive_accuracy: 0.8207, prior_entropy: 0.9509, recall: 0.8207, relative_absolute_error: 0.3861, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4186, root_relative_squared_error: 0.8671, scimark_benchmark: 945.6434, usercpu_time_millis: 108390, usercpu_time_millis_testing: 180, usercpu_time_millis_training: 108210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8148, f_measure: 0.8412, kappa: 0.6545, kb_relative_information_score: 241.8748, mean_absolute_error: 0.1549, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8462, predictive_accuracy: 0.8451, prior_entropy: 0.9509, recall: 0.8451, relative_absolute_error: 0.3323, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3936, root_relative_squared_error: 0.8154, scimark_benchmark: 1028.5889, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4878, f_measure: 0.4875, kb_relative_information_score: -0.1525, mean_absolute_error: 0.4662, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9509, recall: 0.6304, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.0001, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7905, f_measure: 0.8498, kappa: 0.6732, kb_relative_information_score: 189.9933, mean_absolute_error: 0.2422, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8545, predictive_accuracy: 0.8533, prior_entropy: 0.9509, recall: 0.8533, relative_absolute_error: 0.5197, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3593, root_relative_squared_error: 0.7444, scimark_benchmark: 1054.3694, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8534, f_measure: 0.8136, kappa: 0.6031, kb_relative_information_score: 209.8446, mean_absolute_error: 0.1957, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8158, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.4198, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4199, root_relative_squared_error: 0.8699, scimark_benchmark: 945.6434, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8515, f_measure: 0.7983, kappa: 0.5658, kb_relative_information_score: 201.9912, mean_absolute_error: 0.204, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7978, predictive_accuracy: 0.7989, prior_entropy: 0.9509, recall: 0.7989, relative_absolute_error: 0.4377, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.8648, scimark_benchmark: 911.3823, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8179, f_measure: 0.7764, kappa: 0.5254, kb_relative_information_score: 169.0929, mean_absolute_error: 0.2485, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7802, predictive_accuracy: 0.7745, prior_entropy: 0.9509, recall: 0.7745, relative_absolute_error: 0.5331, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4132, root_relative_squared_error: 0.8561, scimark_benchmark: 942.6953, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8254, f_measure: 0.7707, kappa: 0.5125, kb_relative_information_score: 164.1862, mean_absolute_error: 0.2557, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7738, predictive_accuracy: 0.769, prior_entropy: 0.9509, recall: 0.769, relative_absolute_error: 0.5485, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8456, scimark_benchmark: 939.7623, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8254, f_measure: 0.7707, kappa: 0.5125, kb_relative_information_score: 164.1862, mean_absolute_error: 0.2557, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7738, predictive_accuracy: 0.769, prior_entropy: 0.9509, recall: 0.769, relative_absolute_error: 0.5485, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8456, scimark_benchmark: 945.6434, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8638, f_measure: 0.8348, kappa: 0.647, kb_relative_information_score: 228.3033, mean_absolute_error: 0.1727, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8357, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.3705, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.384, root_relative_squared_error: 0.7954, scimark_benchmark: 942.1229, usercpu_time_millis: 160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8631, f_measure: 0.8232, kappa: 0.6204, kb_relative_information_score: 223.5928, mean_absolute_error: 0.1787, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8231, predictive_accuracy: 0.8234, prior_entropy: 0.9509, recall: 0.8234, relative_absolute_error: 0.3834, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3854, root_relative_squared_error: 0.7985, scimark_benchmark: 926.6717, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8645, f_measure: 0.8372, kappa: 0.6512, kb_relative_information_score: 225.4332, mean_absolute_error: 0.1783, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8375, predictive_accuracy: 0.837, prior_entropy: 0.9509, recall: 0.837, relative_absolute_error: 0.3824, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3851, root_relative_squared_error: 0.7979, scimark_benchmark: 876.8277, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8604, f_measure: 0.8266, kappa: 0.629, kb_relative_information_score: 218.5617, mean_absolute_error: 0.1863, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8273, predictive_accuracy: 0.8261, prior_entropy: 0.9509, recall: 0.8261, relative_absolute_error: 0.3996, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3902, root_relative_squared_error: 0.8084, scimark_benchmark: 939.7623, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8433, f_measure: 0.8171, kappa: 0.6129, kb_relative_information_score: 215.9056, mean_absolute_error: 0.1878, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.4029, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4144, root_relative_squared_error: 0.8586, scimark_benchmark: 933.8635, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8335, f_measure: 0.8117, kappa: 0.5945, kb_relative_information_score: 197.2632, mean_absolute_error: 0.2173, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8113, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.4661, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3951, root_relative_squared_error: 0.8185, scimark_benchmark: 933.8635, usercpu_time_millis: 200, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8431, f_measure: 0.8336, kappa: 0.6415, kb_relative_information_score: 199.0747, mean_absolute_error: 0.2188, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8332, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.4694, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3802, root_relative_squared_error: 0.7877, scimark_benchmark: 933.8635, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8479, f_measure: 0.8281, kappa: 0.6298, kb_relative_information_score: 186.1917, mean_absolute_error: 0.2365, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8277, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.5074, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3764, root_relative_squared_error: 0.7798, scimark_benchmark: 932.3943, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8434, f_measure: 0.8195, kappa: 0.6104, kb_relative_information_score: 173.2941, mean_absolute_error: 0.2543, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8191, predictive_accuracy: 0.8207, prior_entropy: 0.9509, recall: 0.8207, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3824, root_relative_squared_error: 0.7922, scimark_benchmark: 931.2336, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8514, f_measure: 0.8175, kappa: 0.6075, kb_relative_information_score: 167.7407, mean_absolute_error: 0.2639, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8172, predictive_accuracy: 0.8179, prior_entropy: 0.9509, recall: 0.8179, relative_absolute_error: 0.5661, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3729, root_relative_squared_error: 0.7725, scimark_benchmark: 938.9865, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4878, f_measure: 0.4875, kb_relative_information_score: -0.1525, mean_absolute_error: 0.4662, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9509, recall: 0.6304, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.0001, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8278, f_measure: 0.7707, kappa: 0.5005, kb_relative_information_score: 169.4418, mean_absolute_error: 0.2543, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7742, predictive_accuracy: 0.7772, prior_entropy: 0.9509, recall: 0.7772, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4005, root_relative_squared_error: 0.8297, scimark_benchmark: 938.9865, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.847, f_measure: 0.8121, kappa: 0.5958, kb_relative_information_score: 168.8912, mean_absolute_error: 0.2587, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8117, predictive_accuracy: 0.8125, prior_entropy: 0.9509, recall: 0.8125, relative_absolute_error: 0.5549, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3843, root_relative_squared_error: 0.7961, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8889, f_measure: 0.8323, kappa: 0.6371, kb_relative_information_score: 165.7626, mean_absolute_error: 0.2713, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8327, predictive_accuracy: 0.8342, prior_entropy: 0.9509, recall: 0.8342, relative_absolute_error: 0.5821, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3506, root_relative_squared_error: 0.7264, scimark_benchmark: 943.6956, usercpu_time_millis: 70, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4878, f_measure: 0.4875, kb_relative_information_score: -0.1525, mean_absolute_error: 0.4662, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9509, recall: 0.6304, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4827, root_relative_squared_error: 1.0001, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8458, f_measure: 0.8178, kappa: 0.6087, kb_relative_information_score: 154.7201, mean_absolute_error: 0.2829, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8177, predictive_accuracy: 0.8179, prior_entropy: 0.9509, recall: 0.8179, relative_absolute_error: 0.6069, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.378, root_relative_squared_error: 0.7831, scimark_benchmark: 929.0255, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4875, kb_relative_information_score: 67.3595, mean_absolute_error: 0.3696, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9509, recall: 0.6304, relative_absolute_error: 0.7928, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.6079, root_relative_squared_error: 1.2594, scimark_benchmark: 929.0255, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.861, build_cpu_time: 5.7331, build_memory: 1045307359.3696, f_measure: 0.8272, kappa: 0.6264, kb_relative_information_score: 215.5567, mean_absolute_error: 0.1927, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8271, predictive_accuracy: 0.8288, prior_entropy: 0.9509, recall: 0.8288, relative_absolute_error: 0.4134, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3809, root_relative_squared_error: 0.7891, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8588, build_cpu_time: 11.3097, build_memory: 293352314.1087, f_measure: 0.8364, kappa: 0.648, kb_relative_information_score: 227.0383, mean_absolute_error: 0.1764, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8361, predictive_accuracy: 0.837, prior_entropy: 0.9509, recall: 0.837, relative_absolute_error: 0.3784, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3853, root_relative_squared_error: 0.7982, scimark_benchmark: 940.5537,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8247, build_cpu_time: 70.2755, build_memory: 43395419.7391, f_measure: 0.8313, kappa: 0.6373, kb_relative_information_score: 229.9184, mean_absolute_error: 0.1697, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.831, predictive_accuracy: 0.8315, prior_entropy: 0.9509, recall: 0.8315, relative_absolute_error: 0.364, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4107, root_relative_squared_error: 0.8509, scimark_benchmark: 943.4163,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.849, build_cpu_time: 33.6713, build_memory: 142952835.9348, f_measure: 0.8421, kappa: 0.6607, kb_relative_information_score: 238.8039, mean_absolute_error: 0.159, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.842, predictive_accuracy: 0.8424, prior_entropy: 0.9509, recall: 0.8424, relative_absolute_error: 0.3412, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3944, root_relative_squared_error: 0.817, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8518, build_cpu_time: 16.2039, build_memory: 1242636913.2174, f_measure: 0.8396, kappa: 0.6554, kb_relative_information_score: 234.1502, mean_absolute_error: 0.1651, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8394, predictive_accuracy: 0.8397, prior_entropy: 0.9509, recall: 0.8397, relative_absolute_error: 0.3541, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3956, root_relative_squared_error: 0.8196, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8631, build_cpu_time: 7.5853, build_memory: 864876875.3043, f_measure: 0.8209, kappa: 0.6163, kb_relative_information_score: 220.7155, mean_absolute_error: 0.1815, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8212, predictive_accuracy: 0.8207, prior_entropy: 0.9509, recall: 0.8207, relative_absolute_error: 0.3893, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4058, root_relative_squared_error: 0.8407, scimark_benchmark: 944.4197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, build_cpu_time: 0.9432, build_memory: 605904154.8913, f_measure: 0.7951, kappa: 0.5549, kb_relative_information_score: 195.2089, mean_absolute_error: 0.2166, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7964, predictive_accuracy: 0.7989, prior_entropy: 0.9509, recall: 0.7989, relative_absolute_error: 0.4646, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.8501, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, build_cpu_time: 0.7509, build_memory: 125277375.6522, f_measure: 0.7951, kappa: 0.5549, kb_relative_information_score: 195.2089, mean_absolute_error: 0.2166, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7964, predictive_accuracy: 0.7989, prior_entropy: 0.9509, recall: 0.7989, relative_absolute_error: 0.4646, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.8501, scimark_benchmark: 899.2335,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8591, build_cpu_time: 0.1613, build_memory: 2097651993.5217, f_measure: 0.8258, kappa: 0.6256, kb_relative_information_score: 223.0176, mean_absolute_error: 0.1796, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8256, predictive_accuracy: 0.8261, prior_entropy: 0.9509, recall: 0.8261, relative_absolute_error: 0.3853, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3842, root_relative_squared_error: 0.796, scimark_benchmark: 916.1588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8582, build_cpu_time: 0.0883, build_memory: 1565966026.8044, f_measure: 0.816, kappa: 0.607, kb_relative_information_score: 210.5289, mean_absolute_error: 0.1974, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8172, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.4234, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.8157, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8563, build_cpu_time: 0.0809, build_memory: 913360683.7609, f_measure: 0.8149, kappa: 0.6022, kb_relative_information_score: 212.7823, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8147, predictive_accuracy: 0.8152, prior_entropy: 0.9509, recall: 0.8152, relative_absolute_error: 0.4153, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3893, root_relative_squared_error: 0.8066, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8638, build_cpu_time: 0.1714, build_memory: 413065856.8261, f_measure: 0.8261, kappa: 0.6268, kb_relative_information_score: 218.2179, mean_absolute_error: 0.1862, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.8261, predictive_accuracy: 0.8261, prior_entropy: 0.9509, recall: 0.8261, relative_absolute_error: 0.3995, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3912, root_relative_squared_error: 0.8105, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8545, build_cpu_time: 0.3239, build_memory: 835110662.6087, f_measure: 0.8223, kappa: 0.6169, kb_relative_information_score: 221.0347, mean_absolute_error: 0.1818, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.822, predictive_accuracy: 0.8234, prior_entropy: 0.9509, recall: 0.8234, relative_absolute_error: 0.3901, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4016, root_relative_squared_error: 0.832, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8552, build_cpu_time: 0.4463, build_memory: 78577903.5652, f_measure: 0.8301, kappa: 0.6329, kb_relative_information_score: 228.5002, mean_absolute_error: 0.1722, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.83, predictive_accuracy: 0.8315, prior_entropy: 0.9509, recall: 0.8315, relative_absolute_error: 0.3694, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3934, root_relative_squared_error: 0.8151, scimark_benchmark: 934.8107,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8521, build_cpu_time: 0.5032, build_memory: 272780558.3261, f_measure: 0.8301, kappa: 0.6329, kb_relative_information_score: 228.2955, mean_absolute_error: 0.1725, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.83, predictive_accuracy: 0.8315, prior_entropy: 0.9509, recall: 0.8315, relative_absolute_error: 0.3701, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.8157, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7675, build_cpu_time: 0.1173, build_memory: 502918451.6522, f_measure: 0.7778, kappa: 0.5247, kb_relative_information_score: 185.7364, mean_absolute_error: 0.2245, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7787, predictive_accuracy: 0.7772, prior_entropy: 0.9509, recall: 0.7772, relative_absolute_error: 0.4815, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4706, root_relative_squared_error: 0.975, scimark_benchmark: 937.5625,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7675, build_cpu_time: 0.1629, build_memory: 681045254.0435, f_measure: 0.7778, kappa: 0.5247, kb_relative_information_score: 185.7364, mean_absolute_error: 0.2245, mean_prior_absolute_error: 0.4662, number_of_instances: 368, precision: 0.7787, predictive_accuracy: 0.7772, prior_entropy: 0.9509, recall: 0.7772, relative_absolute_error: 0.4815, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4706, root_relative_squared_error: 0.975, scimark_benchmark: 939.0159,

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