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File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
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File: /var/www/openml/index.php
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Function: require_once

OpenML
Task
Supervised Classification on ionosphere

Supervised Classification on ionosphere

Task 57 Supervised Classification ionosphere 1206 runs submitted
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Visibility: Public
  • basic mythbusting mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_29 study_30 study_41 study_50 study_7 study_73 under100k under1m
Issue #Downvotes for this reason By


Metric:

1206 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9396, build_cpu_time: 0.8519, build_memory: 931423708.8091, f_measure: 0.9363, kappa: 0.8599, kb_relative_information_score: 299.9176, mean_absolute_error: 0.0646, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9397, predictive_accuracy: 0.9373, prior_entropy: 0.9425, recall: 0.9373, relative_absolute_error: 0.1403, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.247, root_relative_squared_error: 0.5149, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9455, build_cpu_time: 0.6589, build_memory: 1035837368.2963, f_measure: 0.9333, kappa: 0.8533, kb_relative_information_score: 297.5408, mean_absolute_error: 0.0674, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9371, predictive_accuracy: 0.9345, prior_entropy: 0.9425, recall: 0.9345, relative_absolute_error: 0.1463, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2516, root_relative_squared_error: 0.5245, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9538, build_cpu_time: 0.2815, build_memory: 1577516908.8775, f_measure: 0.9127, kappa: 0.8076, kb_relative_information_score: 284.032, mean_absolute_error: 0.0845, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9177, predictive_accuracy: 0.9145, prior_entropy: 0.9425, recall: 0.9145, relative_absolute_error: 0.1836, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2802, root_relative_squared_error: 0.5841, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9504, build_cpu_time: 0.2462, build_memory: 242279097.6638, f_measure: 0.9394, kappa: 0.867, kb_relative_information_score: 302.3977, mean_absolute_error: 0.0616, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9415, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1338, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2386, root_relative_squared_error: 0.4975, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9289, build_cpu_time: 0.3729, build_memory: 119411253.2422, f_measure: 0.9306, kappa: 0.8477, kb_relative_information_score: 299.056, mean_absolute_error: 0.0654, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.933, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.1421, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2482, root_relative_squared_error: 0.5174, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9284, build_cpu_time: 0.7458, build_memory: 1074788110.2906, f_measure: 0.9335, kappa: 0.8538, kb_relative_information_score: 299.5846, mean_absolute_error: 0.0647, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9363, predictive_accuracy: 0.9345, prior_entropy: 0.9425, recall: 0.9345, relative_absolute_error: 0.1405, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.253, root_relative_squared_error: 0.5275, scimark_benchmark: 919.8064,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9152, build_cpu_time: 1.3735, build_memory: 54754191.9088, f_measure: 0.9335, kappa: 0.8538, kb_relative_information_score: 298.5726, mean_absolute_error: 0.0663, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9363, predictive_accuracy: 0.9345, prior_entropy: 0.9425, recall: 0.9345, relative_absolute_error: 0.144, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2564, root_relative_squared_error: 0.5345, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9236, build_cpu_time: 2.8088, build_memory: 375161592.661, f_measure: 0.9394, kappa: 0.867, kb_relative_information_score: 303.5567, mean_absolute_error: 0.0598, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9415, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1299, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2446, root_relative_squared_error: 0.5099, scimark_benchmark: 908.2898,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.805, build_cpu_time: 0.0284, build_memory: 297214895.1339, f_measure: 0.8537, kappa: 0.6757, kb_relative_information_score: 239.4398, mean_absolute_error: 0.1418, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8706, predictive_accuracy: 0.8604, prior_entropy: 0.9425, recall: 0.8604, relative_absolute_error: 0.308, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3725, root_relative_squared_error: 0.7765, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.805, build_cpu_time: 0.0233, build_memory: 314337551.6581, f_measure: 0.8537, kappa: 0.6757, kb_relative_information_score: 239.4398, mean_absolute_error: 0.1418, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8706, predictive_accuracy: 0.8604, prior_entropy: 0.9425, recall: 0.8604, relative_absolute_error: 0.308, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3725, root_relative_squared_error: 0.7765, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.805, build_cpu_time: 0.0324, build_memory: 52098620.4217, f_measure: 0.8537, kappa: 0.6757, kb_relative_information_score: 239.4398, mean_absolute_error: 0.1418, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8706, predictive_accuracy: 0.8604, prior_entropy: 0.9425, recall: 0.8604, relative_absolute_error: 0.308, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3725, root_relative_squared_error: 0.7765, scimark_benchmark: 943.4024,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9346, build_cpu_time: 0.049, build_memory: 385454782.5641, f_measure: 0.9099, kappa: 0.8015, kb_relative_information_score: 233.5829, mean_absolute_error: 0.1659, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9142, predictive_accuracy: 0.9117, prior_entropy: 0.9425, recall: 0.9117, relative_absolute_error: 0.3603, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2749, root_relative_squared_error: 0.573, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9672, build_cpu_time: 0.2977, build_memory: 98293289.2536, f_measure: 0.9395, kappa: 0.8675, kb_relative_information_score: 290.6521, mean_absolute_error: 0.0812, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9409, predictive_accuracy: 0.9402, prior_entropy: 0.9425, recall: 0.9402, relative_absolute_error: 0.1763, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2304, root_relative_squared_error: 0.4803, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9707, build_cpu_time: 0.5263, build_memory: 71645472.9345, f_measure: 0.9247, kappa: 0.8344, kb_relative_information_score: 295.078, mean_absolute_error: 0.0722, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9278, predictive_accuracy: 0.9259, prior_entropy: 0.9425, recall: 0.9259, relative_absolute_error: 0.1568, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2345, root_relative_squared_error: 0.4887, scimark_benchmark: 922.3661,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9382, build_cpu_time: 3.2169, build_memory: 469960453.7208, f_measure: 0.9366, kappa: 0.8609, kb_relative_information_score: 301.3141, mean_absolute_error: 0.0627, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9383, predictive_accuracy: 0.9373, prior_entropy: 0.9425, recall: 0.9373, relative_absolute_error: 0.1361, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2503, root_relative_squared_error: 0.5218, scimark_benchmark: 901.473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, build_cpu_time: 1.6217, build_memory: 739192114.7578, f_measure: 0.9367, kappa: 0.8614, kb_relative_information_score: 304.1502, mean_absolute_error: 0.059, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9378, predictive_accuracy: 0.9373, prior_entropy: 0.9425, recall: 0.9373, relative_absolute_error: 0.1282, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2376, root_relative_squared_error: 0.4953, scimark_benchmark: 937.4026,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9405, build_cpu_time: 0.8012, build_memory: 3014010765.4245, f_measure: 0.931, kappa: 0.8488, kb_relative_information_score: 298.0378, mean_absolute_error: 0.0666, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.932, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.1447, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.25, root_relative_squared_error: 0.5211, scimark_benchmark: 937.2031,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9473, build_cpu_time: 0.4698, build_memory: 827310319.3846, f_measure: 0.9226, kappa: 0.8308, kb_relative_information_score: 288.7374, mean_absolute_error: 0.0786, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9229, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.1707, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2627, root_relative_squared_error: 0.5477, scimark_benchmark: 924.2934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8789, build_cpu_time: 0.8938, build_memory: 297264222.792, f_measure: 0.8463, kappa: 0.6619, kb_relative_information_score: 210.301, mean_absolute_error: 0.1874, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.848, predictive_accuracy: 0.849, prior_entropy: 0.9425, recall: 0.849, relative_absolute_error: 0.4069, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3408, root_relative_squared_error: 0.7104, scimark_benchmark: 945.384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9477, build_cpu_time: 0.6071, build_memory: 441131195.0769, f_measure: 0.9163, kappa: 0.8163, kb_relative_information_score: 285.5863, mean_absolute_error: 0.0829, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.918, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.18, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2745, root_relative_squared_error: 0.5722, scimark_benchmark: 913.4921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9616, build_cpu_time: 0.1088, build_memory: 1032670099.8746, f_measure: 0.9308, kappa: 0.8482, kb_relative_information_score: 291.9635, mean_absolute_error: 0.0753, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9324, predictive_accuracy: 0.9316, prior_entropy: 0.9425, recall: 0.9316, relative_absolute_error: 0.1636, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2552, root_relative_squared_error: 0.532, scimark_benchmark: 939.059,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9822, build_cpu_time: 0.1414, build_memory: 500220135.0199, f_measure: 0.9282, kappa: 0.8428, kb_relative_information_score: 260.0092, mean_absolute_error: 0.1301, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9289, predictive_accuracy: 0.9288, prior_entropy: 0.9425, recall: 0.9288, relative_absolute_error: 0.2825, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2286, root_relative_squared_error: 0.4765, scimark_benchmark: 875.7999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8702, build_cpu_time: 0.0333, build_memory: 674537355.7607, f_measure: 0.8884, kappa: 0.7564, kb_relative_information_score: 238.0036, mean_absolute_error: 0.1548, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8883, predictive_accuracy: 0.8889, prior_entropy: 0.9425, recall: 0.8889, relative_absolute_error: 0.3362, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3135, root_relative_squared_error: 0.6535, scimark_benchmark: 936.8525,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8359, build_cpu_time: 0.025, build_memory: 854531009.2308, f_measure: 0.8697, kappa: 0.7115, kb_relative_information_score: 251.8659, mean_absolute_error: 0.1254, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8823, predictive_accuracy: 0.8746, prior_entropy: 0.9425, recall: 0.8746, relative_absolute_error: 0.2722, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3541, root_relative_squared_error: 0.7381, scimark_benchmark: 915.7861,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9275, build_cpu_time: 0.0054, build_memory: 321850938.4843, f_measure: 0.8245, kappa: 0.6112, kb_relative_information_score: 183.9892, mean_absolute_error: 0.2317, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8633, predictive_accuracy: 0.8376, prior_entropy: 0.9425, recall: 0.8376, relative_absolute_error: 0.5033, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3424, root_relative_squared_error: 0.7138, scimark_benchmark: 942.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9286, build_cpu_time: 0.0019, build_memory: 362748035.7607, f_measure: 0.8176, kappa: 0.596, kb_relative_information_score: 183.6232, mean_absolute_error: 0.2321, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.8594, predictive_accuracy: 0.8319, prior_entropy: 0.9425, recall: 0.8319, relative_absolute_error: 0.5041, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.3456, root_relative_squared_error: 0.7204, scimark_benchmark: 813.0234,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9778, build_cpu_time: 18.5241, build_memory: 1156444511.2251, f_measure: 0.9215, kappa: 0.8271, kb_relative_information_score: 273.4002, mean_absolute_error: 0.1063, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9262, predictive_accuracy: 0.9231, prior_entropy: 0.9425, recall: 0.9231, relative_absolute_error: 0.2309, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2349, root_relative_squared_error: 0.4897, scimark_benchmark: 942.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9738, f_measure: 0.9308, kappa: 0.8482, kb_relative_information_score: 0.7393, mean_absolute_error: 0.1316, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9324, predictive_accuracy: 0.9316, prior_entropy: 0.9418, recall: 0.9316, relative_absolute_error: 0.2857, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2326, root_relative_squared_error: 0.4848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9802, build_cpu_time: 37.175, build_memory: 2763588335.7037, f_measure: 0.9155, kappa: 0.8136, kb_relative_information_score: 274.0577, mean_absolute_error: 0.106, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9212, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2302, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2307, root_relative_squared_error: 0.4809, scimark_benchmark: 944.2629,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9221, build_cpu_time: 2.6513, build_memory: 1571195755.0769, f_measure: 0.9277, kappa: 0.8411, kb_relative_information_score: 294.5667, mean_absolute_error: 0.0712, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9304, predictive_accuracy: 0.9288, prior_entropy: 0.9425, recall: 0.9288, relative_absolute_error: 0.1547, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2669, root_relative_squared_error: 0.5563, scimark_benchmark: 945.6653,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9221, build_cpu_time: 1.9537, build_memory: 136794419.5328, f_measure: 0.9277, kappa: 0.8411, kb_relative_information_score: 294.5667, mean_absolute_error: 0.0712, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9304, predictive_accuracy: 0.9288, prior_entropy: 0.9425, recall: 0.9288, relative_absolute_error: 0.1547, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2669, root_relative_squared_error: 0.5563, scimark_benchmark: 941.2105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9399, build_cpu_time: 1.1358, build_memory: 185411510.7009, f_measure: 0.9189, kappa: 0.8217, kb_relative_information_score: 289.5341, mean_absolute_error: 0.0773, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9219, predictive_accuracy: 0.9202, prior_entropy: 0.9425, recall: 0.9202, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2684, root_relative_squared_error: 0.5595, scimark_benchmark: 936.9135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9339, build_cpu_time: 0.5637, build_memory: 573975283.2137, f_measure: 0.9079, kappa: 0.7984, kb_relative_information_score: 278.9697, mean_absolute_error: 0.0908, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9087, predictive_accuracy: 0.9088, prior_entropy: 0.9425, recall: 0.9088, relative_absolute_error: 0.1973, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2938, root_relative_squared_error: 0.6125, scimark_benchmark: 897.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.966, build_cpu_time: 2.7362, build_memory: 2625982839.3618, f_measure: 0.9105, kappa: 0.8036, kb_relative_information_score: 257.2508, mean_absolute_error: 0.1313, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9122, predictive_accuracy: 0.9117, prior_entropy: 0.9425, recall: 0.9117, relative_absolute_error: 0.2851, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2488, root_relative_squared_error: 0.5186, scimark_benchmark: 936.215,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, build_cpu_time: 4.2514, build_memory: 28311701.5157, f_measure: 0.9165, kappa: 0.817, kb_relative_information_score: 258.767, mean_absolute_error: 0.1291, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9176, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2805, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2459, root_relative_squared_error: 0.5126, scimark_benchmark: 941.1698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9746, build_cpu_time: 1.5854, build_memory: 34399213.8348, f_measure: 0.9124, kappa: 0.8069, kb_relative_information_score: 265.288, mean_absolute_error: 0.1183, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9187, predictive_accuracy: 0.9145, prior_entropy: 0.9425, recall: 0.9145, relative_absolute_error: 0.2568, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2401, root_relative_squared_error: 0.5006, scimark_benchmark: 946.172,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9748, build_cpu_time: 0.7382, build_memory: 701876370.2108, f_measure: 0.9157, kappa: 0.8143, kb_relative_information_score: 264.8894, mean_absolute_error: 0.1191, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9202, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2587, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2408, root_relative_squared_error: 0.502, scimark_benchmark: 946.5415,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9745, build_cpu_time: 0.4136, build_memory: 2123338623.0199, f_measure: 0.9159, kappa: 0.815, kb_relative_information_score: 263.1119, mean_absolute_error: 0.1202, mean_prior_absolute_error: 0.4604, number_of_instances: 351, precision: 0.9193, predictive_accuracy: 0.9174, prior_entropy: 0.9425, recall: 0.9174, relative_absolute_error: 0.2611, root_mean_prior_squared_error: 0.4797, root_mean_squared_error: 0.2478, root_relative_squared_error: 0.5167, scimark_benchmark: 936.5204,

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