OpenML
Supervised Classification on analcatdata_negotiation

Supervised Classification on analcatdata_negotiation

Task 3762 Supervised Classification analcatdata_negotiation 512 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7669, f_measure: 0.7005, kappa: 0.3636, kb_relative_information_score: -8.9433, mean_absolute_error: 0.4147, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.773, predictive_accuracy: 0.6848, prior_entropy: 0.8651, recall: 0.6848, relative_absolute_error: 1.0178, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4498, root_relative_squared_error: 0.9989, scimark_benchmark: 929.0363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4347, f_measure: 0.5993, kb_relative_information_score: -0.6249, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.5147, predictive_accuracy: 0.7174, prior_entropy: 0.8651, recall: 0.7174, relative_absolute_error: 1.0018, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4509, root_relative_squared_error: 1.0014, scimark_benchmark: 916.6405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8205, f_measure: 0.8321, kappa: 0.6077, kb_relative_information_score: 39.4779, mean_absolute_error: 0.2279, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8508, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.5594, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3738, root_relative_squared_error: 0.8302, scimark_benchmark: 938.0414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8738, f_measure: 0.7946, kappa: 0.4965, kb_relative_information_score: 38.8387, mean_absolute_error: 0.2287, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.796, predictive_accuracy: 0.7935, prior_entropy: 0.8651, recall: 0.7935, relative_absolute_error: 0.5613, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.8051, scimark_benchmark: 880.8372, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8173, f_measure: 0.8409, kappa: 0.62, kb_relative_information_score: 43.8833, mean_absolute_error: 0.2065, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.85, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.5066, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3796, root_relative_squared_error: 0.843, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8738, f_measure: 0.7946, kappa: 0.4965, kb_relative_information_score: 38.8387, mean_absolute_error: 0.2287, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.796, predictive_accuracy: 0.7935, prior_entropy: 0.8651, recall: 0.7935, relative_absolute_error: 0.5613, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3625, root_relative_squared_error: 0.8051, scimark_benchmark: 1336.2976,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9056, f_measure: 0.8578, kappa: 0.6474, kb_relative_information_score: 33.1274, mean_absolute_error: 0.2669, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8572, predictive_accuracy: 0.8587, prior_entropy: 0.8651, recall: 0.8587, relative_absolute_error: 0.6549, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.34, root_relative_squared_error: 0.755, scimark_benchmark: 1028.5889, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9038, f_measure: 0.8088, kappa: 0.5161, kb_relative_information_score: 30.6025, mean_absolute_error: 0.279, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8081, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.6847, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3469, root_relative_squared_error: 0.7704, scimark_benchmark: 938.9967, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9152, f_measure: 0.8152, kappa: 0.527, kb_relative_information_score: 29.4949, mean_absolute_error: 0.2855, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8209, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.7006, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3475, root_relative_squared_error: 0.7718, scimark_benchmark: 942.6843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8954, f_measure: 0.8043, kappa: 0.5175, kb_relative_information_score: 44.5224, mean_absolute_error: 0.1926, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8043, predictive_accuracy: 0.8043, prior_entropy: 0.8651, recall: 0.8043, relative_absolute_error: 0.4726, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3808, root_relative_squared_error: 0.8456, scimark_benchmark: 925.4974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.891, f_measure: 0.8019, kappa: 0.506, kb_relative_information_score: 44.0151, mean_absolute_error: 0.2024, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8003, predictive_accuracy: 0.8043, prior_entropy: 0.8651, recall: 0.8043, relative_absolute_error: 0.4968, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3612, root_relative_squared_error: 0.8022, scimark_benchmark: 1404.1865, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8971, f_measure: 0.8296, kappa: 0.5902, kb_relative_information_score: 43.7642, mean_absolute_error: 0.2083, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8364, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.5113, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3271, root_relative_squared_error: 0.7264, scimark_benchmark: 1369.9744,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.891, f_measure: 0.8395, kappa: 0.6115, kb_relative_information_score: 43.26, mean_absolute_error: 0.2101, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.844, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.5156, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3319, root_relative_squared_error: 0.7372, scimark_benchmark: 1307.3269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.833, f_measure: 0.8609, kappa: 0.6633, kb_relative_information_score: 46.4772, mean_absolute_error: 0.1994, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8651, predictive_accuracy: 0.8587, prior_entropy: 0.8651, recall: 0.8587, relative_absolute_error: 0.4893, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.7694, scimark_benchmark: 918.6005, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8791, f_measure: 0.8478, kappa: 0.6247, kb_relative_information_score: 50.9669, mean_absolute_error: 0.1708, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8478, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.4193, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3934, root_relative_squared_error: 0.8737, scimark_benchmark: 915.9693, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8875, f_measure: 0.836, kappa: 0.5932, kb_relative_information_score: 48.7758, mean_absolute_error: 0.1769, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8352, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.4342, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3905, root_relative_squared_error: 0.8673, scimark_benchmark: 934.1747, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8942, f_measure: 0.828, kappa: 0.5809, kb_relative_information_score: 47.5541, mean_absolute_error: 0.1826, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8307, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.448, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3824, root_relative_squared_error: 0.8492, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.896, f_measure: 0.8495, kappa: 0.6333, kb_relative_information_score: 47.8442, mean_absolute_error: 0.1826, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.852, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.4481, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.359, root_relative_squared_error: 0.7974, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9135, f_measure: 0.8379, kappa: 0.6025, kb_relative_information_score: 50.4922, mean_absolute_error: 0.1749, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.839, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.4291, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3337, root_relative_squared_error: 0.7411, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8132, f_measure: 0.7413, kappa: 0.3453, kb_relative_information_score: 27.1553, mean_absolute_error: 0.2707, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.7374, predictive_accuracy: 0.75, prior_entropy: 0.8651, recall: 0.75, relative_absolute_error: 0.6642, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3943, root_relative_squared_error: 0.8756, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8124, f_measure: 0.7946, kappa: 0.4965, kb_relative_information_score: 33.9851, mean_absolute_error: 0.2412, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.796, predictive_accuracy: 0.7935, prior_entropy: 0.8651, recall: 0.7935, relative_absolute_error: 0.5919, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3925, root_relative_squared_error: 0.8716, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7314, f_measure: 0.8055, kappa: 0.5038, kb_relative_information_score: 46.3909, mean_absolute_error: 0.1848, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8077, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.4535, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4299, root_relative_squared_error: 0.9546, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5993, kb_relative_information_score: 22.5864, mean_absolute_error: 0.2826, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.5147, predictive_accuracy: 0.7174, prior_entropy: 0.8651, recall: 0.7174, relative_absolute_error: 0.6935, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.5316, root_relative_squared_error: 1.1806, scimark_benchmark: 887.6719,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7698, f_measure: 0.8313, kappa: 0.573, kb_relative_information_score: 51.6808, mean_absolute_error: 0.163, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8317, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.4001, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4038, root_relative_squared_error: 0.8967, scimark_benchmark: 1297.6599, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9228, f_measure: 0.8296, kappa: 0.5902, kb_relative_information_score: 45.9638, mean_absolute_error: 0.1964, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8364, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.482, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3261, root_relative_squared_error: 0.7241, scimark_benchmark: 1335.643, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5787, f_measure: 0.661, kappa: 0.1592, kb_relative_information_score: 9.3617, mean_absolute_error: 0.337, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.6591, predictive_accuracy: 0.663, prior_entropy: 0.8651, recall: 0.663, relative_absolute_error: 0.8269, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.5805, root_relative_squared_error: 1.2891, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9353, f_measure: 0.8495, kappa: 0.6333, kb_relative_information_score: 48.4201, mean_absolute_error: 0.1901, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.852, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.4666, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3097, root_relative_squared_error: 0.6879, scimark_benchmark: 939.5088, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, f_measure: 0.594, kappa: -0.0214, kb_relative_information_score: 19.9415, mean_absolute_error: 0.2935, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.5124, predictive_accuracy: 0.7065, prior_entropy: 0.8651, recall: 0.7065, relative_absolute_error: 0.7202, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.5417, root_relative_squared_error: 1.2031, scimark_benchmark: 934.0566, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9129, f_measure: 0.8925, kappa: 0.738, kb_relative_information_score: 54.6148, mean_absolute_error: 0.1683, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8946, predictive_accuracy: 0.8913, prior_entropy: 0.8651, recall: 0.8913, relative_absolute_error: 0.413, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3037, root_relative_squared_error: 0.6745, scimark_benchmark: 934.0566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9237, f_measure: 0.8925, kappa: 0.738, kb_relative_information_score: 50.659, mean_absolute_error: 0.1827, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8946, predictive_accuracy: 0.8913, prior_entropy: 0.8651, recall: 0.8913, relative_absolute_error: 0.4483, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3055, root_relative_squared_error: 0.6784, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9266, f_measure: 0.8925, kappa: 0.738, kb_relative_information_score: 51.9443, mean_absolute_error: 0.1773, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8946, predictive_accuracy: 0.8913, prior_entropy: 0.8651, recall: 0.8913, relative_absolute_error: 0.435, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3025, root_relative_squared_error: 0.6718, scimark_benchmark: 893.5298, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8479, f_measure: 0.8163, kappa: 0.5495, kb_relative_information_score: 39.2673, mean_absolute_error: 0.2333, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8175, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.5726, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3616, root_relative_squared_error: 0.8031, scimark_benchmark: 913.4252, usercpu_time_millis: 210, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8922, f_measure: 0.8578, kappa: 0.6474, kb_relative_information_score: 45.4385, mean_absolute_error: 0.1984, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8572, predictive_accuracy: 0.8587, prior_entropy: 0.8651, recall: 0.8587, relative_absolute_error: 0.4868, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3356, root_relative_squared_error: 0.7454, scimark_benchmark: 1280.6952, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8529, f_measure: 0.828, kappa: 0.5809, kb_relative_information_score: 46.5418, mean_absolute_error: 0.1871, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8307, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.459, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3908, root_relative_squared_error: 0.8678, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8354, f_measure: 0.8409, kappa: 0.62, kb_relative_information_score: 39.7867, mean_absolute_error: 0.2311, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.85, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.5671, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3698, root_relative_squared_error: 0.8212, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8575, f_measure: 0.8521, kappa: 0.6492, kb_relative_information_score: 44.8124, mean_absolute_error: 0.207, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8639, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.5081, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3424, root_relative_squared_error: 0.7603, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7931, f_measure: 0.836, kappa: 0.5932, kb_relative_information_score: 51.6808, mean_absolute_error: 0.163, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8352, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.4001, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4038, root_relative_squared_error: 0.8967, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7786, f_measure: 0.7901, kappa: 0.5096, kb_relative_information_score: 38.4561, mean_absolute_error: 0.2174, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8094, predictive_accuracy: 0.7826, prior_entropy: 0.8651, recall: 0.7826, relative_absolute_error: 0.5335, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4663, root_relative_squared_error: 1.0354, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8447, f_measure: 0.8296, kappa: 0.5902, kb_relative_information_score: 42.2387, mean_absolute_error: 0.2116, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8364, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.5193, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3844, root_relative_squared_error: 0.8536, scimark_benchmark: 1358.4523,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8674, build_cpu_time: 0.0266, build_memory: 103950491.2174, f_measure: 0.8239, kappa: 0.5609, kb_relative_information_score: 49.4561, mean_absolute_error: 0.1732, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8226, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.425, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3944, root_relative_squared_error: 0.8759, scimark_benchmark: 907.3828,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9105, build_cpu_time: 0.1125, build_memory: 370633013.6522, f_measure: 0.8459, kappa: 0.6158, kb_relative_information_score: 53.9491, mean_absolute_error: 0.1558, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8449, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.3824, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3604, root_relative_squared_error: 0.8004, scimark_benchmark: 946.9091,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8939, build_cpu_time: 0.3961, build_memory: 537817902, f_measure: 0.8338, kappa: 0.5833, kb_relative_information_score: 52.2076, mean_absolute_error: 0.1616, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8327, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.3966, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3662, root_relative_squared_error: 0.8131, scimark_benchmark: 943.7751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8939, build_cpu_time: 0.3453, build_memory: 808632108.9565, f_measure: 0.8338, kappa: 0.5833, kb_relative_information_score: 52.2076, mean_absolute_error: 0.1616, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8327, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.3966, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3662, root_relative_squared_error: 0.8131, scimark_benchmark: 915.8564,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7949, build_cpu_time: 0.0152, build_memory: 907916661.7391, f_measure: 0.7967, kappa: 0.5079, kb_relative_information_score: 39.5964, mean_absolute_error: 0.2148, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8017, predictive_accuracy: 0.7935, prior_entropy: 0.8651, recall: 0.7935, relative_absolute_error: 0.5271, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4459, root_relative_squared_error: 0.9903, scimark_benchmark: 927.3354,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8185, build_cpu_time: 0.0108, build_memory: 212750249.0435, f_measure: 0.7609, kappa: 0.4103, kb_relative_information_score: 33.5686, mean_absolute_error: 0.2372, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.7609, predictive_accuracy: 0.7609, prior_entropy: 0.8651, recall: 0.7609, relative_absolute_error: 0.582, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4594, root_relative_squared_error: 1.0201, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.803, build_cpu_time: 0.0039, build_memory: 1669559280, f_measure: 0.7704, kappa: 0.4304, kb_relative_information_score: 35.5795, mean_absolute_error: 0.2327, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.7692, predictive_accuracy: 0.7717, prior_entropy: 0.8651, recall: 0.7717, relative_absolute_error: 0.5711, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4452, root_relative_squared_error: 0.9886, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7777, build_cpu_time: 0.0018, build_memory: 564239896.7826, f_measure: 0.7635, kappa: 0.4237, kb_relative_information_score: 29.3819, mean_absolute_error: 0.255, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.7668, predictive_accuracy: 0.7609, prior_entropy: 0.8651, recall: 0.7609, relative_absolute_error: 0.6259, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4481, root_relative_squared_error: 0.9951, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8505, build_cpu_time: 0.0024, build_memory: 545593425.5652, f_measure: 0.8379, kappa: 0.6025, kb_relative_information_score: 48.3541, mean_absolute_error: 0.1875, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.839, predictive_accuracy: 0.837, prior_entropy: 0.8651, recall: 0.837, relative_absolute_error: 0.4602, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3704, root_relative_squared_error: 0.8226, scimark_benchmark: 943.2074,

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