OpenML
Supervised Classification on tic-tac-toe

Supervised Classification on tic-tac-toe

Task 1813 Supervised Classification tic-tac-toe 366 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, f_measure: 0.9673, kappa: 0.9276, kb_relative_information_score: 3566.2108, mean_absolute_error: 0.1367, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9674, predictive_accuracy: 0.9674, prior_entropy: 0.9312, recall: 0.9674, relative_absolute_error: 0.3017, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1967, root_relative_squared_error: 0.4133, scimark_benchmark: 1330.0694, usercpu_time_millis: 13820, usercpu_time_millis_testing: 190, usercpu_time_millis_training: 13630,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7393, f_measure: 0.6849, kappa: 0.2881, kb_relative_information_score: 873.6141, mean_absolute_error: 0.3701, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.686, predictive_accuracy: 0.7002, prior_entropy: 0.9312, recall: 0.7002, relative_absolute_error: 0.8169, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4348, root_relative_squared_error: 0.9136, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8543, f_measure: 0.8007, kappa: 0.5546, kb_relative_information_score: 2285.0684, mean_absolute_error: 0.2374, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.8005, predictive_accuracy: 0.804, prior_entropy: 0.9312, recall: 0.804, relative_absolute_error: 0.524, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3825, root_relative_squared_error: 0.8037, scimark_benchmark: 1315.3881, usercpu_time_millis: 630, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.982, f_measure: 0.9164, kappa: 0.8126, kb_relative_information_score: 2372.0965, mean_absolute_error: 0.2561, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9206, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5654, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3005, root_relative_squared_error: 0.6314, scimark_benchmark: 1301.9956, usercpu_time_millis: 100, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7769, f_measure: 0.7803, kappa: 0.5162, kb_relative_information_score: 2385.9861, mean_absolute_error: 0.2182, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.781, predictive_accuracy: 0.7797, prior_entropy: 0.9312, recall: 0.7797, relative_absolute_error: 0.4816, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4489, root_relative_squared_error: 0.9434, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8253, f_measure: 0.7907, kappa: 0.5292, kb_relative_information_score: 2133.4026, mean_absolute_error: 0.2524, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7938, predictive_accuracy: 0.7973, prior_entropy: 0.9312, recall: 0.7973, relative_absolute_error: 0.5572, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.8185, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9396, f_measure: 0.8952, kappa: 0.7667, kb_relative_information_score: 3455.0211, mean_absolute_error: 0.1266, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.8956, predictive_accuracy: 0.8962, prior_entropy: 0.9312, recall: 0.8962, relative_absolute_error: 0.2794, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.2919, root_relative_squared_error: 0.6133, scimark_benchmark: 1327.6929, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7463, f_measure: 0.7723, kappa: 0.4957, kb_relative_information_score: 2288.1479, mean_absolute_error: 0.2269, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7717, predictive_accuracy: 0.7731, prior_entropy: 0.9312, recall: 0.7731, relative_absolute_error: 0.5009, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4764, root_relative_squared_error: 1.0011, scimark_benchmark: 1315.395, usercpu_time_millis: 110, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8987, f_measure: 0.8708, kappa: 0.7318, kb_relative_information_score: 3330.1525, mean_absolute_error: 0.1324, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9042, predictive_accuracy: 0.8676, prior_entropy: 0.9312, recall: 0.8676, relative_absolute_error: 0.2922, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3638, root_relative_squared_error: 0.7645, scimark_benchmark: 1384.4418, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9445, f_measure: 0.9122, kappa: 0.8056, kb_relative_information_score: 3702.0197, mean_absolute_error: 0.1028, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9121, predictive_accuracy: 0.9125, prior_entropy: 0.9312, recall: 0.9125, relative_absolute_error: 0.227, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.2759, root_relative_squared_error: 0.5797, scimark_benchmark: 1341.2341, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9824, f_measure: 0.9774, kappa: 0.9505, kb_relative_information_score: 4537.7737, mean_absolute_error: 0.0228, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9786, predictive_accuracy: 0.9772, prior_entropy: 0.9312, recall: 0.9772, relative_absolute_error: 0.0502, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1509, root_relative_squared_error: 0.317, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6709, f_measure: 0.7002, kappa: 0.34, kb_relative_information_score: 1476.1663, mean_absolute_error: 0.3006, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7011, predictive_accuracy: 0.6994, prior_entropy: 0.9312, recall: 0.6994, relative_absolute_error: 0.6636, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5483, root_relative_squared_error: 1.1522, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8275, f_measure: 0.8473, kappa: 0.6613, kb_relative_information_score: 3113.9307, mean_absolute_error: 0.152, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.8469, predictive_accuracy: 0.848, prior_entropy: 0.9312, recall: 0.848, relative_absolute_error: 0.3355, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3899, root_relative_squared_error: 0.8192, scimark_benchmark: 1028.5889, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5165, kb_relative_information_score: -2.0868, mean_absolute_error: 0.4531, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.427, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4759, root_relative_squared_error: 1, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8502, f_measure: 0.8145, kappa: 0.5847, kb_relative_information_score: 2560.6159, mean_absolute_error: 0.2096, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.8153, predictive_accuracy: 0.8182, prior_entropy: 0.9312, recall: 0.8182, relative_absolute_error: 0.4627, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3802, root_relative_squared_error: 0.7991, scimark_benchmark: 1054.3694, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, build_cpu_time: 2.2483, build_memory: 412238729.6, f_measure: 0.9726, kappa: 0.9396, kb_relative_information_score: 4478.555, mean_absolute_error: 0.0283, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9726, predictive_accuracy: 0.9727, prior_entropy: 0.9312, recall: 0.9727, relative_absolute_error: 0.0626, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1455, root_relative_squared_error: 0.3057, scimark_benchmark: 924.2934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9971, build_cpu_time: 2.1993, build_memory: 669615083.2, f_measure: 0.9724, kappa: 0.9391, kb_relative_information_score: 4477.6661, mean_absolute_error: 0.0284, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9724, predictive_accuracy: 0.9724, prior_entropy: 0.9312, recall: 0.9724, relative_absolute_error: 0.0627, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1451, root_relative_squared_error: 0.305, scimark_benchmark: 895.3841,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9974, build_cpu_time: 1.8271, build_memory: 1238910804.8, f_measure: 0.9722, kappa: 0.9386, kb_relative_information_score: 4474.5798, mean_absolute_error: 0.0288, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9722, predictive_accuracy: 0.9722, prior_entropy: 0.9312, recall: 0.9722, relative_absolute_error: 0.0635, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1454, root_relative_squared_error: 0.3055, scimark_benchmark: 927.1482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9975, build_cpu_time: 1.1464, build_memory: 816068413.6, f_measure: 0.9729, kappa: 0.94, kb_relative_information_score: 4474.4443, mean_absolute_error: 0.0288, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9728, predictive_accuracy: 0.9729, prior_entropy: 0.9312, recall: 0.9729, relative_absolute_error: 0.0635, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.143, root_relative_squared_error: 0.3005, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9974, build_cpu_time: 0.6006, build_memory: 941165922.4, f_measure: 0.9729, kappa: 0.94, kb_relative_information_score: 4472.4004, mean_absolute_error: 0.0292, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9728, predictive_accuracy: 0.9729, prior_entropy: 0.9312, recall: 0.9729, relative_absolute_error: 0.0645, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1387, root_relative_squared_error: 0.2915, scimark_benchmark: 943.1873,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9633, build_cpu_time: 0.0177, build_memory: 895932083.2, f_measure: 0.9065, kappa: 0.7919, kb_relative_information_score: 3646.1968, mean_absolute_error: 0.108, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9068, predictive_accuracy: 0.9073, prior_entropy: 0.9312, recall: 0.9073, relative_absolute_error: 0.2384, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.2688, root_relative_squared_error: 0.5648, scimark_benchmark: 935.1201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9852, build_cpu_time: 0.0298, build_memory: 814360284.8, f_measure: 0.9434, kappa: 0.8743, kb_relative_information_score: 4104.8004, mean_absolute_error: 0.0641, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9439, predictive_accuracy: 0.9438, prior_entropy: 0.9312, recall: 0.9438, relative_absolute_error: 0.1414, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.2134, root_relative_squared_error: 0.4483, scimark_benchmark: 943.1873,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9929, build_cpu_time: 0.0686, build_memory: 1058945313.6, f_measure: 0.9677, kappa: 0.9285, kb_relative_information_score: 4415.8211, mean_absolute_error: 0.0346, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9678, predictive_accuracy: 0.9679, prior_entropy: 0.9312, recall: 0.9679, relative_absolute_error: 0.0764, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1644, root_relative_squared_error: 0.3456, scimark_benchmark: 939.1359,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9947, build_cpu_time: 0.1391, build_memory: 1310405551.2, f_measure: 0.9803, kappa: 0.9565, kb_relative_information_score: 4565.6243, mean_absolute_error: 0.0205, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9804, predictive_accuracy: 0.9804, prior_entropy: 0.9312, recall: 0.9804, relative_absolute_error: 0.0451, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1317, root_relative_squared_error: 0.2768, scimark_benchmark: 927.1482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.993, build_cpu_time: 0.2358, build_memory: 2079269750.4, f_measure: 0.9843, kappa: 0.9654, kb_relative_information_score: 4618.2707, mean_absolute_error: 0.0155, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9843, predictive_accuracy: 0.9843, prior_entropy: 0.9312, recall: 0.9843, relative_absolute_error: 0.0342, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.119, root_relative_squared_error: 0.25, scimark_benchmark: 915.3856,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7459, build_cpu_time: 0.0061, build_memory: 126059550.4, f_measure: 0.7572, kappa: 0.4637, kb_relative_information_score: 2115.9768, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7571, predictive_accuracy: 0.7572, prior_entropy: 0.9312, recall: 0.7572, relative_absolute_error: 0.536, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4766, root_relative_squared_error: 1.0016, scimark_benchmark: 947.5446,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7459, build_cpu_time: 0.0042, build_memory: 1743993176, f_measure: 0.7572, kappa: 0.4637, kb_relative_information_score: 2115.9768, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7571, predictive_accuracy: 0.7572, prior_entropy: 0.9312, recall: 0.7572, relative_absolute_error: 0.536, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4766, root_relative_squared_error: 1.0016, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7459, build_cpu_time: 0.0019, build_memory: 2474280379.2, f_measure: 0.7572, kappa: 0.4637, kb_relative_information_score: 2115.9768, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7571, predictive_accuracy: 0.7572, prior_entropy: 0.9312, recall: 0.7572, relative_absolute_error: 0.536, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4766, root_relative_squared_error: 1.0016, scimark_benchmark: 946.9091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7459, build_cpu_time: 0.0024, build_memory: 673004688, f_measure: 0.7572, kappa: 0.4637, kb_relative_information_score: 2115.9768, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7571, predictive_accuracy: 0.7572, prior_entropy: 0.9312, recall: 0.7572, relative_absolute_error: 0.536, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4766, root_relative_squared_error: 1.0016, scimark_benchmark: 946.9091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7459, build_cpu_time: 0.0022, build_memory: 652222697.6, f_measure: 0.7572, kappa: 0.4637, kb_relative_information_score: 2115.9768, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.7571, predictive_accuracy: 0.7572, prior_entropy: 0.9312, recall: 0.7572, relative_absolute_error: 0.536, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4766, root_relative_squared_error: 1.0016, scimark_benchmark: 946.9091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0622, build_memory: 1468574936, f_measure: 0.9162, kappa: 0.8119, kb_relative_information_score: 2358.8115, mean_absolute_error: 0.2576, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9215, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5686, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3012, root_relative_squared_error: 0.633, scimark_benchmark: 939.9709,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0919, build_memory: 2238346180, f_measure: 0.9162, kappa: 0.8119, kb_relative_information_score: 2358.8115, mean_absolute_error: 0.2576, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9215, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5686, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3012, root_relative_squared_error: 0.633, scimark_benchmark: 924.9295,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0953, build_memory: 245747062.4, f_measure: 0.9162, kappa: 0.8119, kb_relative_information_score: 2358.8115, mean_absolute_error: 0.2576, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9215, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5686, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3012, root_relative_squared_error: 0.633, scimark_benchmark: 940.5537,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0929, build_memory: 1088831892.8, f_measure: 0.9162, kappa: 0.8119, kb_relative_information_score: 2358.8115, mean_absolute_error: 0.2576, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9215, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5686, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3012, root_relative_squared_error: 0.633, scimark_benchmark: 942.3945,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, build_cpu_time: 0.0727, build_memory: 1273511356.8, f_measure: 0.9162, kappa: 0.8119, kb_relative_information_score: 2358.8115, mean_absolute_error: 0.2576, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9215, predictive_accuracy: 0.9182, prior_entropy: 0.9312, recall: 0.9182, relative_absolute_error: 0.5686, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.3012, root_relative_squared_error: 0.633, scimark_benchmark: 937.5757,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9695, build_cpu_time: 0.069, build_memory: 240432481.6, f_measure: 0.9002, kappa: 0.7759, kb_relative_information_score: 2924.201, mean_absolute_error: 0.1924, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.9056, predictive_accuracy: 0.9027, prior_entropy: 0.9312, recall: 0.9027, relative_absolute_error: 0.4248, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.2754, root_relative_squared_error: 0.5787, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9234, build_cpu_time: 0.0483, build_memory: 1325575813.6, f_measure: 0.8197, kappa: 0.5928, kb_relative_information_score: 2229.7783, mean_absolute_error: 0.2532, mean_prior_absolute_error: 0.453, number_of_instances: 4790, precision: 0.8318, predictive_accuracy: 0.8282, prior_entropy: 0.9312, recall: 0.8282, relative_absolute_error: 0.559, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.336, root_relative_squared_error: 0.7062, scimark_benchmark: 939.0159,
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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

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From your own software

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

OpenML APIs