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Function: require_once

OpenML
Task
Supervised Classification on lowbwt

Supervised Classification on lowbwt

Task 3804 Supervised Classification lowbwt 555 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 study_7 under100k under1m
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555 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8208, f_measure: 0.7927, kappa: 0.5845, kb_relative_information_score: 88.3176, mean_absolute_error: 0.2729, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.7954, predictive_accuracy: 0.7937, prior_entropy: 0.9984, recall: 0.7937, relative_absolute_error: 0.5471, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4161, root_relative_squared_error: 0.8331, scimark_benchmark: 1325.2092,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8192, f_measure: 0.8217, kappa: 0.6459, kb_relative_information_score: 122.7817, mean_absolute_error: 0.1746, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8442, predictive_accuracy: 0.8254, prior_entropy: 0.9984, recall: 0.8254, relative_absolute_error: 0.35, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4179, root_relative_squared_error: 0.8367, scimark_benchmark: 1312.3073, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8278, f_measure: 0.83, kappa: 0.666, kb_relative_information_score: 126.7945, mean_absolute_error: 0.164, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8751, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.3288, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.405, root_relative_squared_error: 0.8109, scimark_benchmark: 1336.3256, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8444, f_measure: 0.8474, kappa: 0.6988, kb_relative_information_score: 132.8138, mean_absolute_error: 0.1481, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8845, predictive_accuracy: 0.8519, prior_entropy: 0.9984, recall: 0.8519, relative_absolute_error: 0.297, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3849, root_relative_squared_error: 0.7707, scimark_benchmark: 1287.514, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, f_measure: 0.8325, kappa: 0.6673, kb_relative_information_score: 105.2069, mean_absolute_error: 0.2345, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8556, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.47, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3495, root_relative_squared_error: 0.6999, scimark_benchmark: 930.5999, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7879, f_measure: 0.7899, kappa: 0.5819, kb_relative_information_score: 110.7431, mean_absolute_error: 0.2063, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8069, predictive_accuracy: 0.7937, prior_entropy: 0.9984, recall: 0.7937, relative_absolute_error: 0.4136, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4543, root_relative_squared_error: 0.9095, scimark_benchmark: 942.6843, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8611, f_measure: 0.8064, kappa: 0.6143, kb_relative_information_score: 100.1545, mean_absolute_error: 0.2479, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8223, predictive_accuracy: 0.8095, prior_entropy: 0.9984, recall: 0.8095, relative_absolute_error: 0.497, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3554, root_relative_squared_error: 0.7115, scimark_benchmark: 908.2231, usercpu_time_millis: 720, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 690,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8552, f_measure: 0.8188, kappa: 0.6372, kb_relative_information_score: 104.4494, mean_absolute_error: 0.2335, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8243, predictive_accuracy: 0.8201, prior_entropy: 0.9984, recall: 0.8201, relative_absolute_error: 0.4681, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3642, root_relative_squared_error: 0.7293, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8698, f_measure: 0.8082, kappa: 0.6159, kb_relative_information_score: 102.6635, mean_absolute_error: 0.2406, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8135, predictive_accuracy: 0.8095, prior_entropy: 0.9984, recall: 0.8095, relative_absolute_error: 0.4823, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3563, root_relative_squared_error: 0.7134, scimark_benchmark: 1363.434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8395, f_measure: 0.8129, kappa: 0.626, kb_relative_information_score: 98.9867, mean_absolute_error: 0.249, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8216, predictive_accuracy: 0.8148, prior_entropy: 0.9984, recall: 0.8148, relative_absolute_error: 0.4991, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3777, root_relative_squared_error: 0.7563, scimark_benchmark: 1304.6687, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8644, f_measure: 0.856, kappa: 0.7117, kb_relative_information_score: 102.7818, mean_absolute_error: 0.2413, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8632, predictive_accuracy: 0.8571, prior_entropy: 0.9984, recall: 0.8571, relative_absolute_error: 0.4838, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3587, root_relative_squared_error: 0.7182, scimark_benchmark: 1280.6952, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7946, f_measure: 0.7884, kappa: 0.5758, kb_relative_information_score: 109.2202, mean_absolute_error: 0.2104, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.7884, predictive_accuracy: 0.7884, prior_entropy: 0.9984, recall: 0.7884, relative_absolute_error: 0.4217, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4544, root_relative_squared_error: 0.9099, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8007, f_measure: 0.8262, kappa: 0.6561, kb_relative_information_score: 102.4458, mean_absolute_error: 0.2415, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8562, predictive_accuracy: 0.8307, prior_entropy: 0.9984, recall: 0.8307, relative_absolute_error: 0.484, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3684, root_relative_squared_error: 0.7376, scimark_benchmark: 1315.3881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8315, f_measure: 0.8279, kappa: 0.6571, kb_relative_information_score: 105.7494, mean_absolute_error: 0.2322, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8447, predictive_accuracy: 0.8307, prior_entropy: 0.9984, recall: 0.8307, relative_absolute_error: 0.4654, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3636, root_relative_squared_error: 0.728, scimark_benchmark: 1327.6929, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8182, f_measure: 0.8197, kappa: 0.6383, kb_relative_information_score: 120.7752, mean_absolute_error: 0.1799, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8209, predictive_accuracy: 0.8201, prior_entropy: 0.9984, recall: 0.8201, relative_absolute_error: 0.3606, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4241, root_relative_squared_error: 0.8492, scimark_benchmark: 1372.2145, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6212, f_measure: 0.6051, kappa: 0.2385, kb_relative_information_score: 42.5248, mean_absolute_error: 0.3862, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.6361, predictive_accuracy: 0.6138, prior_entropy: 0.9984, recall: 0.6138, relative_absolute_error: 0.7742, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.6215, root_relative_squared_error: 1.2444, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8398, f_measure: 0.8036, kappa: 0.6062, kb_relative_information_score: 106.9596, mean_absolute_error: 0.2224, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8052, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.4458, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.8018, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8278, f_measure: 0.83, kappa: 0.666, kb_relative_information_score: 126.7945, mean_absolute_error: 0.164, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8751, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.3288, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.405, root_relative_squared_error: 0.8109, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8394, f_measure: 0.8422, kappa: 0.6882, kb_relative_information_score: 130.8074, mean_absolute_error: 0.1534, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.876, predictive_accuracy: 0.8466, prior_entropy: 0.9984, recall: 0.8466, relative_absolute_error: 0.3076, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3917, root_relative_squared_error: 0.7843, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4955, f_measure: 0.3601, kb_relative_information_score: -0.0083, mean_absolute_error: 0.4989, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.2744, predictive_accuracy: 0.5238, prior_entropy: 0.9984, recall: 0.5238, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4994, root_relative_squared_error: 1, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8093, f_measure: 0.8283, kappa: 0.6575, kb_relative_information_score: 104.5374, mean_absolute_error: 0.2354, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8418, predictive_accuracy: 0.8307, prior_entropy: 0.9984, recall: 0.8307, relative_absolute_error: 0.4719, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3611, root_relative_squared_error: 0.7231, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8385, f_measure: 0.8026, kappa: 0.605, kb_relative_information_score: 113.0039, mean_absolute_error: 0.2009, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8089, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.4027, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4394, root_relative_squared_error: 0.8799, scimark_benchmark: 931.2336, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8366, f_measure: 0.7924, kappa: 0.5841, kb_relative_information_score: 111.7207, mean_absolute_error: 0.2035, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.7966, predictive_accuracy: 0.7937, prior_entropy: 0.9984, recall: 0.7937, relative_absolute_error: 0.4078, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4354, root_relative_squared_error: 0.8718, scimark_benchmark: 945.6434, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8556, f_measure: 0.8026, kappa: 0.605, kb_relative_information_score: 107.8861, mean_absolute_error: 0.2195, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8089, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.4399, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.383, root_relative_squared_error: 0.7669, scimark_benchmark: 876.8277, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8472, f_measure: 0.8133, kappa: 0.6263, kb_relative_information_score: 104.591, mean_absolute_error: 0.2308, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8197, predictive_accuracy: 0.8148, prior_entropy: 0.9984, recall: 0.8148, relative_absolute_error: 0.4627, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3812, root_relative_squared_error: 0.7633, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8489, f_measure: 0.8129, kappa: 0.626, kb_relative_information_score: 103.1381, mean_absolute_error: 0.2349, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8216, predictive_accuracy: 0.8148, prior_entropy: 0.9984, recall: 0.8148, relative_absolute_error: 0.4709, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3828, root_relative_squared_error: 0.7664, scimark_benchmark: 894.7455, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8811, f_measure: 0.8313, kappa: 0.6667, kb_relative_information_score: 127.8391, mean_absolute_error: 0.1616, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8643, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.3239, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3834, root_relative_squared_error: 0.7677, scimark_benchmark: 936.7115, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8703, f_measure: 0.8365, kappa: 0.6773, kb_relative_information_score: 127.1037, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8727, predictive_accuracy: 0.8413, prior_entropy: 0.9984, recall: 0.8413, relative_absolute_error: 0.3305, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3817, root_relative_squared_error: 0.7643, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8728, f_measure: 0.83, kappa: 0.666, kb_relative_information_score: 126.4248, mean_absolute_error: 0.1656, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8751, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.332, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3917, root_relative_squared_error: 0.7844, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8593, f_measure: 0.83, kappa: 0.666, kb_relative_information_score: 124.1707, mean_absolute_error: 0.1731, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8751, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.347, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.392, root_relative_squared_error: 0.7848, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8337, f_measure: 0.83, kappa: 0.666, kb_relative_information_score: 126.279, mean_absolute_error: 0.1659, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8751, predictive_accuracy: 0.836, prior_entropy: 0.9984, recall: 0.836, relative_absolute_error: 0.3325, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4028, root_relative_squared_error: 0.8064, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.903, f_measure: 0.8197, kappa: 0.6383, kb_relative_information_score: 117.4677, mean_absolute_error: 0.1914, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8209, predictive_accuracy: 0.8201, prior_entropy: 0.9984, recall: 0.8201, relative_absolute_error: 0.3836, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3679, root_relative_squared_error: 0.7366, scimark_benchmark: 933.8635, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9057, f_measure: 0.8191, kappa: 0.6376, kb_relative_information_score: 114.2891, mean_absolute_error: 0.2007, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8228, predictive_accuracy: 0.8201, prior_entropy: 0.9984, recall: 0.8201, relative_absolute_error: 0.4024, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3545, root_relative_squared_error: 0.7098, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8638, build_cpu_time: 1.2801, build_memory: 710778281.5661, f_measure: 0.7881, kappa: 0.5749, kb_relative_information_score: 109.1965, mean_absolute_error: 0.2117, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.7885, predictive_accuracy: 0.7884, prior_entropy: 0.9984, recall: 0.7884, relative_absolute_error: 0.4243, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4101, root_relative_squared_error: 0.8212, scimark_benchmark: 886.4678,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8337, build_cpu_time: 2.1761, build_memory: 636873597.164, f_measure: 0.8092, kappa: 0.6174, kb_relative_information_score: 116.2379, mean_absolute_error: 0.1918, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8097, predictive_accuracy: 0.8095, prior_entropy: 0.9984, recall: 0.8095, relative_absolute_error: 0.3844, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4278, root_relative_squared_error: 0.8567, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8622, build_cpu_time: 1.1422, build_memory: 379830170.5397, f_measure: 0.8095, kappa: 0.6182, kb_relative_information_score: 115.7392, mean_absolute_error: 0.194, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8095, predictive_accuracy: 0.8095, prior_entropy: 0.9984, recall: 0.8095, relative_absolute_error: 0.3889, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4285, root_relative_squared_error: 0.8579, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.856, build_cpu_time: 0.1763, build_memory: 1148366060.0635, f_measure: 0.7984, kappa: 0.5957, kb_relative_information_score: 112.408, mean_absolute_error: 0.2025, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.7995, predictive_accuracy: 0.7989, prior_entropy: 0.9984, recall: 0.7989, relative_absolute_error: 0.406, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.4239, root_relative_squared_error: 0.8489, scimark_benchmark: 923.3659,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8807, build_cpu_time: 0.0226, build_memory: 320608876.4021, f_measure: 0.8038, kappa: 0.6066, kb_relative_information_score: 114.6, mean_absolute_error: 0.1979, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8046, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.3966, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.7798, scimark_benchmark: 945.0532,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8807, build_cpu_time: 0.0189, build_memory: 149273033.2275, f_measure: 0.8038, kappa: 0.6066, kb_relative_information_score: 114.6, mean_absolute_error: 0.1979, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8046, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.3966, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.7798, scimark_benchmark: 935.6292,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8807, build_cpu_time: 0.0168, build_memory: 1303665240.0847, f_measure: 0.8038, kappa: 0.6066, kb_relative_information_score: 114.6, mean_absolute_error: 0.1979, mean_prior_absolute_error: 0.4989, number_of_instances: 189, precision: 0.8046, predictive_accuracy: 0.8042, prior_entropy: 0.9984, recall: 0.8042, relative_absolute_error: 0.3966, root_mean_prior_squared_error: 0.4994, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.7798, scimark_benchmark: 933.4498,

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