OpenML
Supervised Classification on BNG(tic-tac-toe)

Supervised Classification on BNG(tic-tac-toe)

Task 322 Supervised Classification BNG(tic-tac-toe) 238 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
Issue #Downvotes for this reason By


Metric:

238 Runs

Fetching data
Fetching data
Search runs in more detail
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7594, f_measure: 0.7163, kappa: 0.36, kb_relative_information_score: 2675.8123, mean_absolute_error: 0.3648, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7195, predictive_accuracy: 0.7294, prior_entropy: 0.9315, recall: 0.7294, relative_absolute_error: 0.8048, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4273, root_relative_squared_error: 0.8975, scimark_benchmark: 880.8372, usercpu_time_millis: 11560, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 11490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6695, f_measure: 0.717, kappa: 0.3619, kb_relative_information_score: 4901.4179, mean_absolute_error: 0.2708, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7193, predictive_accuracy: 0.7292, prior_entropy: 0.9315, recall: 0.7292, relative_absolute_error: 0.5975, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.5204, root_relative_squared_error: 1.0932, scimark_benchmark: 1304.9611, usercpu_time_millis: 3640, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 3570,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8328, f_measure: 0.7661, kappa: 0.4739, kb_relative_information_score: 4109.6718, mean_absolute_error: 0.3179, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7684, predictive_accuracy: 0.7737, prior_entropy: 0.9315, recall: 0.7737, relative_absolute_error: 0.7013, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3937, root_relative_squared_error: 0.827, scimark_benchmark: 1310.3951, usercpu_time_millis: 140, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7419, f_measure: 0.7817, kappa: 0.5092, kb_relative_information_score: 6676.4102, mean_absolute_error: 0.2114, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7845, predictive_accuracy: 0.7886, prior_entropy: 0.9315, recall: 0.7886, relative_absolute_error: 0.4664, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4598, root_relative_squared_error: 0.9658, scimark_benchmark: 1368.9272, usercpu_time_millis: 369120, usercpu_time_millis_testing: 158200, usercpu_time_millis_training: 210920,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.751, f_measure: 0.7106, kappa: 0.3494, kb_relative_information_score: 2782.919, mean_absolute_error: 0.3578, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7097, predictive_accuracy: 0.7196, prior_entropy: 0.9315, recall: 0.7196, relative_absolute_error: 0.7893, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4325, root_relative_squared_error: 0.9085, scimark_benchmark: 1337.7959, usercpu_time_millis: 110, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8641, f_measure: 0.8012, kappa: 0.5561, kb_relative_information_score: 5472.2081, mean_absolute_error: 0.2677, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.8009, predictive_accuracy: 0.8042, prior_entropy: 0.9315, recall: 0.8042, relative_absolute_error: 0.5907, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3729, root_relative_squared_error: 0.7833, scimark_benchmark: 1066.7184, usercpu_time_millis: 8340, usercpu_time_millis_testing: 220, usercpu_time_millis_training: 8120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8409, f_measure: 0.7823, kappa: 0.5158, kb_relative_information_score: 5375.2058, mean_absolute_error: 0.2652, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7813, predictive_accuracy: 0.7843, prior_entropy: 0.9315, recall: 0.7843, relative_absolute_error: 0.5851, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3935, root_relative_squared_error: 0.8266, scimark_benchmark: 1307.4861, usercpu_time_millis: 12970, usercpu_time_millis_testing: 4700, usercpu_time_millis_training: 8270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7887, f_measure: 0.7689, kappa: 0.4945, kb_relative_information_score: 5407.3747, mean_absolute_error: 0.2599, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7715, predictive_accuracy: 0.7672, prior_entropy: 0.9315, recall: 0.7672, relative_absolute_error: 0.5733, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4311, root_relative_squared_error: 0.9056, scimark_benchmark: 1315.3881, usercpu_time_millis: 180, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8272, f_measure: 0.7774, kappa: 0.5043, kb_relative_information_score: 4847.0802, mean_absolute_error: 0.2895, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7764, predictive_accuracy: 0.7799, prior_entropy: 0.9315, recall: 0.7799, relative_absolute_error: 0.6388, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.8325, scimark_benchmark: 1280.6952, usercpu_time_millis: 200, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8291, f_measure: 0.7823, kappa: 0.5144, kb_relative_information_score: 4927.0662, mean_absolute_error: 0.2887, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7816, predictive_accuracy: 0.7855, prior_entropy: 0.9315, recall: 0.7855, relative_absolute_error: 0.6369, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3936, root_relative_squared_error: 0.8269, scimark_benchmark: 1361.1055, usercpu_time_millis: 24050, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 23990,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5526, f_measure: 0.4894, kappa: 0.086, kb_relative_information_score: -2138.772, mean_absolute_error: 0.5065, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.6072, predictive_accuracy: 0.4935, prior_entropy: 0.9315, recall: 0.4935, relative_absolute_error: 1.1176, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.7117, root_relative_squared_error: 1.495, scimark_benchmark: 1384.4418, usercpu_time_millis: 1290, usercpu_time_millis_testing: 160, usercpu_time_millis_training: 1130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8433, f_measure: 0.7919, kappa: 0.5378, kb_relative_information_score: 5402.6243, mean_absolute_error: 0.2701, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.791, predictive_accuracy: 0.7935, prior_entropy: 0.9315, recall: 0.7935, relative_absolute_error: 0.5959, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3893, root_relative_squared_error: 0.8177, scimark_benchmark: 1341.2341, usercpu_time_millis: 6880, usercpu_time_millis_testing: 700, usercpu_time_millis_training: 6180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6734, f_measure: 0.7029, kappa: 0.3456, kb_relative_information_score: 4103.591, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7034, predictive_accuracy: 0.7025, prior_entropy: 0.9315, recall: 0.7025, relative_absolute_error: 0.6565, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.5455, root_relative_squared_error: 1.1458, scimark_benchmark: 1465.2979, usercpu_time_millis: 40, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6762, f_measure: 0.7324, kappa: 0.3958, kb_relative_information_score: 5708.4416, mean_absolute_error: 0.2438, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.761, predictive_accuracy: 0.7562, prior_entropy: 0.9315, recall: 0.7562, relative_absolute_error: 0.5379, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4938, root_relative_squared_error: 1.0372, scimark_benchmark: 977.6382, usercpu_time_millis: 12620, usercpu_time_millis_testing: 420, usercpu_time_millis_training: 12200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5158, kb_relative_information_score: 0.0219, mean_absolute_error: 0.4532, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.4263, predictive_accuracy: 0.6529, prior_entropy: 0.9315, recall: 0.6529, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4761, root_relative_squared_error: 1, scimark_benchmark: 1054.3694, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 1054.3694, usercpu_time_millis: 310, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8431, build_cpu_time: 1316.916, build_memory: 313502432, f_measure: 0.7822, kappa: 0.516, kb_relative_information_score: 5381.5253, mean_absolute_error: 0.2656, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7813, predictive_accuracy: 0.7841, prior_entropy: 0.9315, recall: 0.7841, relative_absolute_error: 0.5859, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.392, root_relative_squared_error: 0.8234, scimark_benchmark: 898.9472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.845, build_cpu_time: 1629.327, build_memory: 1160313312, f_measure: 0.7829, kappa: 0.518, kb_relative_information_score: 5387.1245, mean_absolute_error: 0.2654, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.782, predictive_accuracy: 0.7844, prior_entropy: 0.9315, recall: 0.7844, relative_absolute_error: 0.5855, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3904, root_relative_squared_error: 0.8202, scimark_benchmark: 942.152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8463, build_cpu_time: 3503.549, build_memory: 1121637424, f_measure: 0.7834, kappa: 0.519, kb_relative_information_score: 5389.5929, mean_absolute_error: 0.2655, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7825, predictive_accuracy: 0.785, prior_entropy: 0.9315, recall: 0.785, relative_absolute_error: 0.5858, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3893, root_relative_squared_error: 0.8179, scimark_benchmark: 941.2105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8476, build_cpu_time: 6489.5, build_memory: 1535193336, f_measure: 0.784, kappa: 0.5205, kb_relative_information_score: 5398.7309, mean_absolute_error: 0.2654, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7832, predictive_accuracy: 0.7856, prior_entropy: 0.9315, recall: 0.7856, relative_absolute_error: 0.5855, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3885, root_relative_squared_error: 0.8161, scimark_benchmark: 942.7014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8703, build_cpu_time: 52.397, build_memory: 506472392, f_measure: 0.7925, kappa: 0.5354, kb_relative_information_score: 6770.1656, mean_absolute_error: 0.2103, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7931, predictive_accuracy: 0.797, prior_entropy: 0.9315, recall: 0.797, relative_absolute_error: 0.464, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4111, root_relative_squared_error: 0.8636, scimark_benchmark: 936.9135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8561, build_cpu_time: 34.793, build_memory: 1019348824, f_measure: 0.7721, kappa: 0.4884, kb_relative_information_score: 6283.4115, mean_absolute_error: 0.2258, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7731, predictive_accuracy: 0.7782, prior_entropy: 0.9315, recall: 0.7782, relative_absolute_error: 0.4983, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4318, root_relative_squared_error: 0.907, scimark_benchmark: 938.2803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.845, build_cpu_time: 17.401, build_memory: 2058634504, f_measure: 0.7489, kappa: 0.4351, kb_relative_information_score: 5784.685, mean_absolute_error: 0.2415, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7507, predictive_accuracy: 0.7574, prior_entropy: 0.9315, recall: 0.7574, relative_absolute_error: 0.5328, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4531, root_relative_squared_error: 0.9518, scimark_benchmark: 945.6653,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8032, build_cpu_time: 9.323, build_memory: 178267152, f_measure: 0.7299, kappa: 0.3911, kb_relative_information_score: 5245.0348, mean_absolute_error: 0.2601, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7326, predictive_accuracy: 0.741, prior_entropy: 0.9315, recall: 0.741, relative_absolute_error: 0.5738, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4807, root_relative_squared_error: 1.0097, scimark_benchmark: 938.4414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7686, build_cpu_time: 6.048, build_memory: 133564712, f_measure: 0.7183, kappa: 0.3645, kb_relative_information_score: 4923.1724, mean_absolute_error: 0.2711, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7215, predictive_accuracy: 0.7312, prior_entropy: 0.9315, recall: 0.7312, relative_absolute_error: 0.598, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4963, root_relative_squared_error: 1.0424, scimark_benchmark: 943.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8419, build_cpu_time: 5192.861, build_memory: 2544077272, f_measure: 0.7803, kappa: 0.5047, kb_relative_information_score: 4230.1892, mean_absolute_error: 0.3203, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7875, predictive_accuracy: 0.7898, prior_entropy: 0.9315, recall: 0.7898, relative_absolute_error: 0.7066, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.8182, scimark_benchmark: 945.5753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8583, build_cpu_time: 22.609, build_memory: 381239224, f_measure: 0.7912, kappa: 0.5331, kb_relative_information_score: 4999.9549, mean_absolute_error: 0.2882, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7912, predictive_accuracy: 0.7952, prior_entropy: 0.9315, recall: 0.7952, relative_absolute_error: 0.636, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3773, root_relative_squared_error: 0.7926, scimark_benchmark: 905.8704,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8583, build_cpu_time: 23.626, build_memory: 122863352, f_measure: 0.7912, kappa: 0.5331, kb_relative_information_score: 4999.9549, mean_absolute_error: 0.2882, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7912, predictive_accuracy: 0.7952, prior_entropy: 0.9315, recall: 0.7952, relative_absolute_error: 0.636, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3773, root_relative_squared_error: 0.7926, scimark_benchmark: 943.2711,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8574, build_cpu_time: 11.006, build_memory: 1278865704, f_measure: 0.7905, kappa: 0.5316, kb_relative_information_score: 4986.2359, mean_absolute_error: 0.2885, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7905, predictive_accuracy: 0.7944, prior_entropy: 0.9315, recall: 0.7944, relative_absolute_error: 0.6366, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3782, root_relative_squared_error: 0.7944, scimark_benchmark: 946.965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8568, build_cpu_time: 5.978, build_memory: 2406223520, f_measure: 0.7901, kappa: 0.5303, kb_relative_information_score: 4984.4874, mean_absolute_error: 0.2886, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7902, predictive_accuracy: 0.7941, prior_entropy: 0.9315, recall: 0.7941, relative_absolute_error: 0.6367, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3784, root_relative_squared_error: 0.7949, scimark_benchmark: 941.6301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8525, build_cpu_time: 2.764, build_memory: 2090099336, f_measure: 0.7881, kappa: 0.5263, kb_relative_information_score: 4964.9182, mean_absolute_error: 0.289, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7878, predictive_accuracy: 0.7918, prior_entropy: 0.9315, recall: 0.7918, relative_absolute_error: 0.6376, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.3803, root_relative_squared_error: 0.7988, scimark_benchmark: 938.0876,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.274, build_memory: 1421502832, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 948.6351,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.261, build_memory: 1434537872, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 923.5258,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.23, build_memory: 143514424, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 930.789,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.239, build_memory: 2120795216, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 944.7199,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.243, build_memory: 2049155648, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 942.5707,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.222, build_memory: 1082742112, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 917.5224,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, build_cpu_time: 0.263, build_memory: 1168552744, f_measure: 0.7784, kappa: 0.5039, kb_relative_information_score: 4574.7178, mean_absolute_error: 0.3027, mean_prior_absolute_error: 0.4533, number_of_instances: 12990, precision: 0.7784, predictive_accuracy: 0.783, prior_entropy: 0.9315, recall: 0.783, relative_absolute_error: 0.6679, root_mean_prior_squared_error: 0.4761, root_mean_squared_error: 0.4022, root_relative_squared_error: 0.8448, scimark_benchmark: 901.5412,

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