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Function: require_once

A PHP Error was encountered

Severity: Warning

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Backtrace:

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Line: 37
Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
Line: 30
Function: sql

File: /var/www/openml/openml_OS/views/pages/frontend/t/pre.php
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Function: query

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Function: loadpage

File: /var/www/openml/index.php
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Function: require_once

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Severity: Warning

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Backtrace:

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
Line: 30
Function: sql

File: /var/www/openml/openml_OS/views/pages/frontend/t/pre.php
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Function: query

File: /var/www/openml/openml_OS/helpers/cms_helper.php
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Function: view

File: /var/www/openml/openml_OS/controllers/Frontend.php
Line: 85
Function: loadpage

File: /var/www/openml/index.php
Line: 337
Function: require_once

OpenML
Task
Supervised Classification on postoperative-patient-data

Supervised Classification on postoperative-patient-data

Task 1798 Supervised Classification postoperative-patient-data 299 runs submitted
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299 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3259, f_measure: 0.5738, kappa: -0.0704, kb_relative_information_score: -63.6902, mean_absolute_error: 0.3116, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5174, predictive_accuracy: 0.6622, prior_entropy: 1.0305, recall: 0.6622, relative_absolute_error: 1.0856, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4358, root_relative_squared_error: 1.1606, scimark_benchmark: 940.3347,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5911, kb_relative_information_score: -9.9187, mean_absolute_error: 0.2914, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 1.015, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3784, root_relative_squared_error: 1.0078, scimark_benchmark: 1372.2145, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4369, f_measure: 0.5553, kappa: -0.1234, kb_relative_information_score: -65.2467, mean_absolute_error: 0.3215, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5156, predictive_accuracy: 0.6111, prior_entropy: 1.0305, recall: 0.6111, relative_absolute_error: 1.1199, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4163, root_relative_squared_error: 1.1088, scimark_benchmark: 939.449, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4734, f_measure: 0.5843, kappa: -0.0455, kb_relative_information_score: -219.1177, mean_absolute_error: 0.4035, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5408, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 1.4057, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4651, root_relative_squared_error: 1.2388, scimark_benchmark: 915.9324, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4369, f_measure: 0.5421, kappa: -0.1336, kb_relative_information_score: -33.0756, mean_absolute_error: 0.2889, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5215, predictive_accuracy: 0.5667, prior_entropy: 1.0305, recall: 0.5667, relative_absolute_error: 1.0064, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.5375, root_relative_squared_error: 1.4314, scimark_benchmark: 916.9356, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3358, f_measure: 0.5565, kappa: -0.1166, kb_relative_information_score: -61.6116, mean_absolute_error: 0.3102, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5148, predictive_accuracy: 0.6156, prior_entropy: 1.0305, recall: 0.6156, relative_absolute_error: 1.0805, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4418, root_relative_squared_error: 1.1766, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3985, f_measure: 0.5554, kappa: -0.1142, kb_relative_information_score: -48.1911, mean_absolute_error: 0.3008, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5233, predictive_accuracy: 0.5978, prior_entropy: 1.0305, recall: 0.5978, relative_absolute_error: 1.048, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4471, root_relative_squared_error: 1.1907, scimark_benchmark: 1066.7184, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3499, f_measure: 0.5297, kappa: -0.1744, kb_relative_information_score: -80.5838, mean_absolute_error: 0.3208, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5011, predictive_accuracy: 0.5644, prior_entropy: 1.0305, recall: 0.5644, relative_absolute_error: 1.1175, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4578, root_relative_squared_error: 1.2191, scimark_benchmark: 1346.9602, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4531, f_measure: 0.5651, kappa: -0.07, kb_relative_information_score: -37.4138, mean_absolute_error: 0.292, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5459, predictive_accuracy: 0.5911, prior_entropy: 1.0305, recall: 0.5911, relative_absolute_error: 1.0173, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.5213, root_relative_squared_error: 1.3885, scimark_benchmark: 1315.0767, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.5886, kappa: -0.0093, kb_relative_information_score: 1.0398, mean_absolute_error: 0.2842, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5054, predictive_accuracy: 0.7044, prior_entropy: 1.0305, recall: 0.7044, relative_absolute_error: 0.99, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3838, root_relative_squared_error: 1.0222, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5911, kb_relative_information_score: 7.1061, mean_absolute_error: 0.2818, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 0.9817, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3754, root_relative_squared_error: 0.9997, scimark_benchmark: 1287.514, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4246, f_measure: 0.5194, kappa: -0.1675, kb_relative_information_score: -66.0927, mean_absolute_error: 0.3111, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5066, predictive_accuracy: 0.5333, prior_entropy: 1.0305, recall: 0.5333, relative_absolute_error: 1.0838, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.5578, root_relative_squared_error: 1.4855, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5022, f_measure: 0.5675, kappa: -0.0026, kb_relative_information_score: -37.521, mean_absolute_error: 0.2933, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5767, predictive_accuracy: 0.56, prior_entropy: 1.0305, recall: 0.56, relative_absolute_error: 1.0219, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.5416, root_relative_squared_error: 1.4424, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3772, f_measure: 0.5403, kappa: -0.1474, kb_relative_information_score: -70.7356, mean_absolute_error: 0.3207, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5136, predictive_accuracy: 0.5733, prior_entropy: 1.0305, recall: 0.5733, relative_absolute_error: 1.1172, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4768, root_relative_squared_error: 1.2697, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4821, f_measure: 0.5843, kappa: -0.0455, kb_relative_information_score: 68.5254, mean_absolute_error: 0.2193, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5408, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 0.7638, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4683, root_relative_squared_error: 1.2471, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4709, f_measure: 0.5752, kappa: -0.073, kb_relative_information_score: 42.5319, mean_absolute_error: 0.237, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5334, predictive_accuracy: 0.6444, prior_entropy: 1.0305, recall: 0.6444, relative_absolute_error: 0.8257, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4869, root_relative_squared_error: 1.2966, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5911, kb_relative_information_score: -11.8471, mean_absolute_error: 0.292, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 1.0171, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3758, root_relative_squared_error: 1.0008, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4755, f_measure: 0.5873, kappa: -0.039, kb_relative_information_score: -13.2295, mean_absolute_error: 0.292, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5481, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 1.0173, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.411, root_relative_squared_error: 1.0945, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3534, build_cpu_time: 0.1957, build_memory: 270982946.4, f_measure: 0.5507, kappa: -0.1296, kb_relative_information_score: -56.2, mean_absolute_error: 0.3063, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5187, predictive_accuracy: 0.5933, prior_entropy: 1.0305, recall: 0.5933, relative_absolute_error: 1.0672, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4907, root_relative_squared_error: 1.307, scimark_benchmark: 932.2022,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3534, build_cpu_time: 0.1423, build_memory: 769475480, f_measure: 0.5507, kappa: -0.1296, kb_relative_information_score: -56.2, mean_absolute_error: 0.3063, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5187, predictive_accuracy: 0.5933, prior_entropy: 1.0305, recall: 0.5933, relative_absolute_error: 1.0672, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4907, root_relative_squared_error: 1.307, scimark_benchmark: 926.9332,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3673, build_cpu_time: 0.0155, build_memory: 96581721.6, f_measure: 0.5863, kappa: -0.0314, kb_relative_information_score: -76.4199, mean_absolute_error: 0.3259, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5481, predictive_accuracy: 0.68, prior_entropy: 1.0305, recall: 0.68, relative_absolute_error: 1.1355, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4215, root_relative_squared_error: 1.1226, scimark_benchmark: 939.0159,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3122, build_cpu_time: 0.0005, build_memory: 340973236, f_measure: 0.5445, kappa: -0.1451, kb_relative_information_score: -67.7917, mean_absolute_error: 0.3137, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5104, predictive_accuracy: 0.5889, prior_entropy: 1.0305, recall: 0.5889, relative_absolute_error: 1.0929, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.453, root_relative_squared_error: 1.2066, scimark_benchmark: 945.8601,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3325, build_memory: 215107172.8, f_measure: 0.5301, kappa: -0.184, kb_relative_information_score: -99.5741, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.4925, predictive_accuracy: 0.5778, prior_entropy: 1.0305, recall: 0.5778, relative_absolute_error: 1.1615, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.5131, root_relative_squared_error: 1.3665, scimark_benchmark: 945.4085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.0341, build_memory: 93366810.4, f_measure: 0.5911, kb_relative_information_score: -9.9187, mean_absolute_error: 0.2914, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 1.015, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3784, root_relative_squared_error: 1.0078, scimark_benchmark: 925.419,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4369, build_cpu_time: 0.0113, build_memory: 1191304790.4, f_measure: 0.5553, kappa: -0.1234, kb_relative_information_score: -65.2467, mean_absolute_error: 0.3215, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5156, predictive_accuracy: 0.6111, prior_entropy: 1.0305, recall: 0.6111, relative_absolute_error: 1.1199, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4163, root_relative_squared_error: 1.1088, scimark_benchmark: 940.4464,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3451, build_cpu_time: 0.0019, build_memory: 482167514.4, f_measure: 0.5695, kappa: -0.0808, kb_relative_information_score: -42.4659, mean_absolute_error: 0.3006, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5067, predictive_accuracy: 0.66, prior_entropy: 1.0305, recall: 0.66, relative_absolute_error: 1.0471, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.411, root_relative_squared_error: 1.0945, scimark_benchmark: 920.6941,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3648, build_cpu_time: 0.003, build_memory: 150556038.4, f_measure: 0.5828, kappa: -0.038, kb_relative_information_score: -98.6845, mean_absolute_error: 0.3374, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.536, predictive_accuracy: 0.68, prior_entropy: 1.0305, recall: 0.68, relative_absolute_error: 1.1755, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4192, root_relative_squared_error: 1.1165, scimark_benchmark: 930.1524,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4821, build_cpu_time: 0.0002, build_memory: 897998083.2, f_measure: 0.5843, kappa: -0.0455, kb_relative_information_score: 68.5254, mean_absolute_error: 0.2193, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5408, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 0.7638, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4683, root_relative_squared_error: 1.2471, scimark_benchmark: 946.8522,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4821, build_cpu_time: 0.0001, build_memory: 924635552, f_measure: 0.5843, kappa: -0.0455, kb_relative_information_score: 68.5254, mean_absolute_error: 0.2193, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5408, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 0.7638, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4683, root_relative_squared_error: 1.2471, scimark_benchmark: 929.8725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4821, build_cpu_time: 0.0002, build_memory: 373444398.4, f_measure: 0.5843, kappa: -0.0455, kb_relative_information_score: 68.5254, mean_absolute_error: 0.2193, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5408, predictive_accuracy: 0.6711, prior_entropy: 1.0305, recall: 0.6711, relative_absolute_error: 0.7638, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4683, root_relative_squared_error: 1.2471, scimark_benchmark: 927.6633,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.0004, build_memory: 630267728, f_measure: 0.5911, kb_relative_information_score: -11.8471, mean_absolute_error: 0.292, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 1.0171, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3758, root_relative_squared_error: 1.0008, scimark_benchmark: 947.7747,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.0003, build_memory: 649377736, f_measure: 0.5911, kb_relative_information_score: -11.8471, mean_absolute_error: 0.292, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5057, predictive_accuracy: 0.7111, prior_entropy: 1.0305, recall: 0.7111, relative_absolute_error: 1.0171, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.3758, root_relative_squared_error: 1.0008, scimark_benchmark: 938.2445,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4214, build_cpu_time: 175.1617, build_memory: 22460308, f_measure: 0.5736, kappa: -0.0647, kb_relative_information_score: -59.3841, mean_absolute_error: 0.3123, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5442, predictive_accuracy: 0.6156, prior_entropy: 1.0305, recall: 0.6156, relative_absolute_error: 1.0879, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4198, root_relative_squared_error: 1.1181, scimark_benchmark: 943.1197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3477, build_cpu_time: 0.0653, build_memory: 844071224, f_measure: 0.558, kappa: -0.1169, kb_relative_information_score: -106.2089, mean_absolute_error: 0.333, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5177, predictive_accuracy: 0.6156, prior_entropy: 1.0305, recall: 0.6156, relative_absolute_error: 1.1602, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4132, root_relative_squared_error: 1.1005, scimark_benchmark: 894.2099,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3452, build_cpu_time: 0.2377, build_memory: 575547899.2, f_measure: 0.5566, kappa: -0.1202, kb_relative_information_score: -107.3019, mean_absolute_error: 0.3339, mean_prior_absolute_error: 0.2871, number_of_instances: 450, precision: 0.5166, predictive_accuracy: 0.6133, prior_entropy: 1.0305, recall: 0.6133, relative_absolute_error: 1.1633, root_mean_prior_squared_error: 0.3755, root_mean_squared_error: 0.4134, root_relative_squared_error: 1.1009, scimark_benchmark: 941.7372,

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