OpenML
Supervised Classification on auto93

Supervised Classification on auto93

Task 3725 Supervised Classification auto93 512 runs submitted
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  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9155, f_measure: 0.893, kappa: 0.7735, kb_relative_information_score: 52.7032, mean_absolute_error: 0.2175, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8944, predictive_accuracy: 0.8925, prior_entropy: 0.9573, recall: 0.8925, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3259, root_relative_squared_error: 0.6726, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8416, f_measure: 0.7984, kappa: 0.5814, kb_relative_information_score: 49.4356, mean_absolute_error: 0.2161, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8101, predictive_accuracy: 0.7957, prior_entropy: 0.9573, recall: 0.7957, relative_absolute_error: 0.4596, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4536, root_relative_squared_error: 0.9363, scimark_benchmark: 899.5042,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9155, f_measure: 0.893, kappa: 0.7735, kb_relative_information_score: 52.7032, mean_absolute_error: 0.2175, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8944, predictive_accuracy: 0.8925, prior_entropy: 0.9573, recall: 0.8925, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3259, root_relative_squared_error: 0.6726, scimark_benchmark: 1299.5783, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.868, f_measure: 0.8502, kappa: 0.6829, kb_relative_information_score: 57.9458, mean_absolute_error: 0.1748, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8518, predictive_accuracy: 0.8495, prior_entropy: 0.9573, recall: 0.8495, relative_absolute_error: 0.3719, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3795, root_relative_squared_error: 0.7834, scimark_benchmark: 899.5042, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8461, f_measure: 0.7331, kappa: 0.4242, kb_relative_information_score: 26.6722, mean_absolute_error: 0.348, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7624, predictive_accuracy: 0.7527, prior_entropy: 0.9573, recall: 0.7527, relative_absolute_error: 0.7403, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4016, root_relative_squared_error: 0.829, scimark_benchmark: 1301.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8367, f_measure: 0.7427, kappa: 0.4458, kb_relative_information_score: 26.2111, mean_absolute_error: 0.3514, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7804, predictive_accuracy: 0.7634, prior_entropy: 0.9573, recall: 0.7634, relative_absolute_error: 0.7476, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4042, root_relative_squared_error: 0.8342, scimark_benchmark: 1330.0694, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.952, f_measure: 0.9023, kappa: 0.7903, kb_relative_information_score: 70.4772, mean_absolute_error: 0.1131, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.9034, predictive_accuracy: 0.9032, prior_entropy: 0.9573, recall: 0.9032, relative_absolute_error: 0.2405, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3083, root_relative_squared_error: 0.6363, scimark_benchmark: 1336.2976, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9079, f_measure: 0.814, kappa: 0.5992, kb_relative_information_score: 55.8418, mean_absolute_error: 0.1834, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8158, predictive_accuracy: 0.8172, prior_entropy: 0.9573, recall: 0.8172, relative_absolute_error: 0.3902, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3736, root_relative_squared_error: 0.7712, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8818, f_measure: 0.8167, kappa: 0.6084, kb_relative_information_score: 52.0763, mean_absolute_error: 0.2092, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8163, predictive_accuracy: 0.8172, prior_entropy: 0.9573, recall: 0.8172, relative_absolute_error: 0.4451, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3777, root_relative_squared_error: 0.7796, scimark_benchmark: 925.4974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8618, f_measure: 0.8038, kappa: 0.5781, kb_relative_information_score: 45.7128, mean_absolute_error: 0.2402, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8044, predictive_accuracy: 0.8065, prior_entropy: 0.9573, recall: 0.8065, relative_absolute_error: 0.5111, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3947, root_relative_squared_error: 0.8146, scimark_benchmark: 937.1527, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.681, f_measure: 0.696, kappa: 0.3451, kb_relative_information_score: 18.8998, mean_absolute_error: 0.3842, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.724, predictive_accuracy: 0.7204, prior_entropy: 0.9573, recall: 0.7204, relative_absolute_error: 0.8172, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4666, root_relative_squared_error: 0.9631, scimark_benchmark: 938.9967, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6675, f_measure: 0.6726, kappa: 0.2947, kb_relative_information_score: 18.2238, mean_absolute_error: 0.3841, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.6957, predictive_accuracy: 0.6989, prior_entropy: 0.9573, recall: 0.6989, relative_absolute_error: 0.817, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4748, root_relative_squared_error: 0.9801, scimark_benchmark: 1315.395, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6436, f_measure: 0.6581, kappa: 0.2649, kb_relative_information_score: 16.9929, mean_absolute_error: 0.3865, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.6833, predictive_accuracy: 0.6882, prior_entropy: 0.9573, recall: 0.6882, relative_absolute_error: 0.8222, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4799, root_relative_squared_error: 0.9906, scimark_benchmark: 912.7324, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8355, f_measure: 0.7772, kappa: 0.5373, kb_relative_information_score: 43.8356, mean_absolute_error: 0.2462, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.789, predictive_accuracy: 0.7742, prior_entropy: 0.9573, recall: 0.7742, relative_absolute_error: 0.5237, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4152, root_relative_squared_error: 0.8571, scimark_benchmark: 869.6028,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9288, f_measure: 0.8692, kappa: 0.7188, kb_relative_information_score: 65.1489, mean_absolute_error: 0.1375, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.871, predictive_accuracy: 0.871, prior_entropy: 0.9573, recall: 0.871, relative_absolute_error: 0.2925, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3416, root_relative_squared_error: 0.7051, scimark_benchmark: 930.5999, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9207, f_measure: 0.8598, kappa: 0.7005, kb_relative_information_score: 62.9194, mean_absolute_error: 0.1493, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8596, predictive_accuracy: 0.8602, prior_entropy: 0.9573, recall: 0.8602, relative_absolute_error: 0.3177, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3463, root_relative_squared_error: 0.7147, scimark_benchmark: 916.6405, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9241, f_measure: 0.8814, kappa: 0.7466, kb_relative_information_score: 63.5155, mean_absolute_error: 0.1499, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8812, predictive_accuracy: 0.8817, prior_entropy: 0.9573, recall: 0.8817, relative_absolute_error: 0.3189, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3213, root_relative_squared_error: 0.6631, scimark_benchmark: 1287.514, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9054, f_measure: 0.8241, kappa: 0.6206, kb_relative_information_score: 56.1531, mean_absolute_error: 0.1852, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8279, predictive_accuracy: 0.828, prior_entropy: 0.9573, recall: 0.828, relative_absolute_error: 0.3941, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3391, root_relative_squared_error: 0.6999, scimark_benchmark: 939.5088, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8993, f_measure: 0.8495, kappa: 0.6793, kb_relative_information_score: 53.8009, mean_absolute_error: 0.2023, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8495, predictive_accuracy: 0.8495, prior_entropy: 0.9573, recall: 0.8495, relative_absolute_error: 0.4303, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3484, root_relative_squared_error: 0.7191, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8751, f_measure: 0.7836, kappa: 0.5366, kb_relative_information_score: 45.223, mean_absolute_error: 0.2421, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.783, predictive_accuracy: 0.7849, prior_entropy: 0.9573, recall: 0.7849, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3615, root_relative_squared_error: 0.7461, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.852, f_measure: 0.7503, kappa: 0.464, kb_relative_information_score: 44.8255, mean_absolute_error: 0.2351, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7495, predictive_accuracy: 0.7527, prior_entropy: 0.9573, recall: 0.7527, relative_absolute_error: 0.5001, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3827, root_relative_squared_error: 0.79, scimark_benchmark: 942.9518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7739, f_measure: 0.7937, kappa: 0.5573, kb_relative_information_score: 51.395, mean_absolute_error: 0.2043, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7935, predictive_accuracy: 0.7957, prior_entropy: 0.9573, recall: 0.7957, relative_absolute_error: 0.4346, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.452, root_relative_squared_error: 0.933, scimark_benchmark: 1312.3073, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4791, kb_relative_information_score: 16.511, mean_absolute_error: 0.3763, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.3889, predictive_accuracy: 0.6237, prior_entropy: 0.9573, recall: 0.6237, relative_absolute_error: 0.8006, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.6135, root_relative_squared_error: 1.2663, scimark_benchmark: 916.6405, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7424, f_measure: 0.762, kappa: 0.4903, kb_relative_information_score: 44.8542, mean_absolute_error: 0.2366, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7612, predictive_accuracy: 0.7634, prior_entropy: 0.9573, recall: 0.7634, relative_absolute_error: 0.5033, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4864, root_relative_squared_error: 1.0039, scimark_benchmark: 1297.6599, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.897, f_measure: 0.8177, kappa: 0.6128, kb_relative_information_score: 49.7014, mean_absolute_error: 0.2221, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8184, predictive_accuracy: 0.8172, prior_entropy: 0.9573, recall: 0.8172, relative_absolute_error: 0.4724, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3606, root_relative_squared_error: 0.7443, scimark_benchmark: 1335.643, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6049, f_measure: 0.6321, kappa: 0.2123, kb_relative_information_score: 18.6912, mean_absolute_error: 0.3656, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.6304, predictive_accuracy: 0.6344, prior_entropy: 0.9573, recall: 0.6344, relative_absolute_error: 0.7778, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.6046, root_relative_squared_error: 1.248, scimark_benchmark: 916.5955, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9025, f_measure: 0.8241, kappa: 0.6206, kb_relative_information_score: 49.028, mean_absolute_error: 0.2278, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8279, predictive_accuracy: 0.828, prior_entropy: 0.9573, recall: 0.828, relative_absolute_error: 0.4846, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3528, root_relative_squared_error: 0.7283, scimark_benchmark: 912.5006, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9204, f_measure: 0.9039, kappa: 0.7973, kb_relative_information_score: 66.4113, mean_absolute_error: 0.1377, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.9066, predictive_accuracy: 0.9032, prior_entropy: 0.9573, recall: 0.9032, relative_absolute_error: 0.293, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3096, root_relative_squared_error: 0.639, scimark_benchmark: 1350.9691, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9143, f_measure: 0.814, kappa: 0.5992, kb_relative_information_score: 39.9882, mean_absolute_error: 0.2816, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8158, predictive_accuracy: 0.8172, prior_entropy: 0.9573, recall: 0.8172, relative_absolute_error: 0.599, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.3522, root_relative_squared_error: 0.7271, scimark_benchmark: 1336.2509, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7209, f_measure: 0.7264, kappa: 0.4106, kb_relative_information_score: 35.5662, mean_absolute_error: 0.2833, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7261, predictive_accuracy: 0.7312, prior_entropy: 0.9573, recall: 0.7312, relative_absolute_error: 0.6027, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4956, root_relative_squared_error: 1.0229, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6456, f_measure: 0.6715, kappa: 0.3107, kb_relative_information_score: 20.1109, mean_absolute_error: 0.3672, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7756, predictive_accuracy: 0.7204, prior_entropy: 0.9573, recall: 0.7204, relative_absolute_error: 0.7811, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4772, root_relative_squared_error: 0.9849, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8034, f_measure: 0.7443, kappa: 0.4624, kb_relative_information_score: 37.5071, mean_absolute_error: 0.2785, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7494, predictive_accuracy: 0.7419, prior_entropy: 0.9573, recall: 0.7419, relative_absolute_error: 0.5925, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4638, root_relative_squared_error: 0.9574, scimark_benchmark: 1290.1085, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.651, f_measure: 0.6858, kappa: 0.3201, kb_relative_information_score: 31.7727, mean_absolute_error: 0.3011, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.6903, predictive_accuracy: 0.6989, prior_entropy: 0.9573, recall: 0.6989, relative_absolute_error: 0.6405, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.5487, root_relative_squared_error: 1.1326, scimark_benchmark: 1341.5768, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5286, f_measure: 0.5262, kappa: 0.0703, kb_relative_information_score: 20.8715, mean_absolute_error: 0.3548, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7738, predictive_accuracy: 0.6452, prior_entropy: 0.9573, recall: 0.6452, relative_absolute_error: 0.7549, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.5957, root_relative_squared_error: 1.2295, scimark_benchmark: 1361.1055, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8377, f_measure: 0.7443, kappa: 0.4624, kb_relative_information_score: 39.8811, mean_absolute_error: 0.2675, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7494, predictive_accuracy: 0.7419, prior_entropy: 0.9573, recall: 0.7419, relative_absolute_error: 0.5691, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.41, root_relative_squared_error: 0.8464, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6369, f_measure: 0.676, kappa: 0.3069, kb_relative_information_score: 33.953, mean_absolute_error: 0.2903, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7196, predictive_accuracy: 0.7097, prior_entropy: 0.9573, recall: 0.7097, relative_absolute_error: 0.6176, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.5388, root_relative_squared_error: 1.1122, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7793, f_measure: 0.7772, kappa: 0.5373, kb_relative_information_score: 47.0345, mean_absolute_error: 0.2258, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.789, predictive_accuracy: 0.7742, prior_entropy: 0.9573, recall: 0.7742, relative_absolute_error: 0.4804, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4752, root_relative_squared_error: 0.9808, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4498, f_measure: 0.4791, kb_relative_information_score: -0.2139, mean_absolute_error: 0.4705, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.3889, predictive_accuracy: 0.6237, prior_entropy: 0.9573, recall: 0.6237, relative_absolute_error: 1.001, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4849, root_relative_squared_error: 1.0009, scimark_benchmark: 1445.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8453, f_measure: 0.7766, kappa: 0.5322, kb_relative_information_score: 43.3509, mean_absolute_error: 0.2491, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.7836, predictive_accuracy: 0.7742, prior_entropy: 0.9573, recall: 0.7742, relative_absolute_error: 0.5299, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4134, root_relative_squared_error: 0.8534, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8924, f_measure: 0.8167, kappa: 0.6084, kb_relative_information_score: 54.8871, mean_absolute_error: 0.1883, mean_prior_absolute_error: 0.4701, number_of_instances: 93, precision: 0.8163, predictive_accuracy: 0.8172, prior_entropy: 0.9573, recall: 0.8172, relative_absolute_error: 0.4005, root_mean_prior_squared_error: 0.4845, root_mean_squared_error: 0.4023, root_relative_squared_error: 0.8305, scimark_benchmark: 931.2336, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
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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