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Function: require_once

OpenML
Task
Supervised Classification on analcatdata_negotiation

Supervised Classification on analcatdata_negotiation

Task 3762 Supervised Classification analcatdata_negotiation 512 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
Issue #Downvotes for this reason By


Metric:

512 Runs

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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,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8357, f_measure: 0.8509, kappa: 0.6414, kb_relative_information_score: 54.3258, mean_absolute_error: 0.1522, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8574, predictive_accuracy: 0.8478, prior_entropy: 0.8651, recall: 0.8478, relative_absolute_error: 0.3734, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3901, root_relative_squared_error: 0.8663, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8281, f_measure: 0.8409, kappa: 0.62, kb_relative_information_score: 51.6808, mean_absolute_error: 0.163, 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: 0.4001, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4038, root_relative_squared_error: 0.8967, scimark_benchmark: 1353.5686,
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: 1330.0803,
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: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8869, f_measure: 0.8459, kappa: 0.6158, kb_relative_information_score: 55.3267, mean_absolute_error: 0.1492, 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: 0.3661, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3717, root_relative_squared_error: 0.8255, scimark_benchmark: 931.2336, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.852, f_measure: 0.8379, kappa: 0.6025, kb_relative_information_score: 48.3278, mean_absolute_error: 0.1877, 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: 0.4606, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3707, root_relative_squared_error: 0.8232, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.852, f_measure: 0.8379, kappa: 0.6025, kb_relative_information_score: 48.3278, mean_absolute_error: 0.1877, 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: 0.4606, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3707, root_relative_squared_error: 0.8232, scimark_benchmark: 923.7642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.852, f_measure: 0.8379, kappa: 0.6025, kb_relative_information_score: 48.3278, mean_absolute_error: 0.1877, 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: 0.4606, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3707, root_relative_squared_error: 0.8232, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8992, f_measure: 0.8163, kappa: 0.5495, kb_relative_information_score: 46.5463, mean_absolute_error: 0.1842, 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: 0.4519, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4156, root_relative_squared_error: 0.923, scimark_benchmark: 936.6206, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9004, f_measure: 0.8261, kappa: 0.5711, kb_relative_information_score: 50.6116, mean_absolute_error: 0.1678, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8261, predictive_accuracy: 0.8261, prior_entropy: 0.8651, recall: 0.8261, relative_absolute_error: 0.4118, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3896, root_relative_squared_error: 0.8652, scimark_benchmark: 938.2848, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.898, f_measure: 0.828, kappa: 0.5809, kb_relative_information_score: 48.951, mean_absolute_error: 0.1749, 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: 0.4293, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3988, root_relative_squared_error: 0.8856, scimark_benchmark: 938.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9004, f_measure: 0.8478, kappa: 0.6247, kb_relative_information_score: 55.3476, mean_absolute_error: 0.1489, 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: 0.3653, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3566, root_relative_squared_error: 0.7919, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8832, f_measure: 0.8833, kappa: 0.7214, kb_relative_information_score: 59.8418, mean_absolute_error: 0.1329, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8918, predictive_accuracy: 0.8804, prior_entropy: 0.8651, recall: 0.8804, relative_absolute_error: 0.3261, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3396, root_relative_squared_error: 0.7541, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.88, f_measure: 0.8141, kappa: 0.5389, kb_relative_information_score: 46.1752, mean_absolute_error: 0.1855, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8132, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.4551, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.9066, scimark_benchmark: 938.4285, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8855, f_measure: 0.7922, kappa: 0.4847, kb_relative_information_score: 43.1981, mean_absolute_error: 0.196, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.7912, predictive_accuracy: 0.7935, prior_entropy: 0.8651, recall: 0.7935, relative_absolute_error: 0.4809, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.9157, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8936, f_measure: 0.8043, kappa: 0.5175, kb_relative_information_score: 44.3834, mean_absolute_error: 0.1911, 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: 0.469, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3921, root_relative_squared_error: 0.8709, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, build_cpu_time: 0.409, build_memory: 25269198.6087, f_measure: 0.7946, kappa: 0.4965, kb_relative_information_score: 42.5723, mean_absolute_error: 0.1982, 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: 0.4865, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4142, root_relative_squared_error: 0.9198, scimark_benchmark: 939.521,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8569, build_cpu_time: 0.3078, build_memory: 140369340.6957, f_measure: 0.8478, kappa: 0.6247, kb_relative_information_score: 51.2996, mean_absolute_error: 0.1665, 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: 0.4087, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3858, root_relative_squared_error: 0.8568, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8558, build_cpu_time: 0.0308, build_memory: 522259588.9565, f_measure: 0.8296, kappa: 0.5902, kb_relative_information_score: 49.1476, mean_absolute_error: 0.1738, 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: 0.4265, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4058, root_relative_squared_error: 0.9013, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.845, build_cpu_time: 0.0529, build_memory: 923984902.7826, f_measure: 0.8296, kappa: 0.5902, kb_relative_information_score: 48.1502, mean_absolute_error: 0.1781, 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: 0.4371, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.4102, root_relative_squared_error: 0.9109, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8339, build_cpu_time: 0.0755, build_memory: 204697552.6087, f_measure: 0.8395, kappa: 0.6115, kb_relative_information_score: 51.035, mean_absolute_error: 0.1669, 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: 0.4095, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3972, root_relative_squared_error: 0.8821, scimark_benchmark: 924.6733,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8339, build_cpu_time: 0.1228, build_memory: 308862233.913, f_measure: 0.8395, kappa: 0.6115, kb_relative_information_score: 50.9036, mean_absolute_error: 0.1675, 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: 0.411, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3976, root_relative_squared_error: 0.883, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8852, build_cpu_time: 0.0138, build_memory: 955807386.7826, f_measure: 0.8141, kappa: 0.5389, kb_relative_information_score: 48.0943, mean_absolute_error: 0.1805, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8132, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.443, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3871, root_relative_squared_error: 0.8596, scimark_benchmark: 945.5885,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8852, build_cpu_time: 0.0195, build_memory: 513627949.8261, f_measure: 0.8141, kappa: 0.5389, kb_relative_information_score: 48.0943, mean_absolute_error: 0.1805, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8132, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.443, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3871, root_relative_squared_error: 0.8596, scimark_benchmark: 890.3066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8852, build_cpu_time: 0.0108, build_memory: 2237576217.0435, f_measure: 0.8141, kappa: 0.5389, kb_relative_information_score: 48.0943, mean_absolute_error: 0.1805, mean_prior_absolute_error: 0.4075, number_of_instances: 92, precision: 0.8132, predictive_accuracy: 0.8152, prior_entropy: 0.8651, recall: 0.8152, relative_absolute_error: 0.443, root_mean_prior_squared_error: 0.4503, root_mean_squared_error: 0.3871, root_relative_squared_error: 0.8596, scimark_benchmark: 916.8516,

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