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OpenML
Task
Supervised Classification on analcatdata_boxing1

Supervised Classification on analcatdata_boxing1

Task 3540 Supervised Classification analcatdata_boxing1 905 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 study_50 study_7 under100k under1m
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905 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8289, f_measure: 0.716, kappa: 0.3642, kb_relative_information_score: 25.9914, mean_absolute_error: 0.3648, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7158, predictive_accuracy: 0.725, prior_entropy: 0.9362, recall: 0.725, relative_absolute_error: 0.8004, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4084, root_relative_squared_error: 0.8561, scimark_benchmark: 854.5188, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7793, f_measure: 0.7932, kappa: 0.5496, kb_relative_information_score: 62.8091, mean_absolute_error: 0.2083, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7958, predictive_accuracy: 0.7917, prior_entropy: 0.9362, recall: 0.7917, relative_absolute_error: 0.4571, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4564, root_relative_squared_error: 0.9569, scimark_benchmark: 889.3151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8178, f_measure: 0.8402, kappa: 0.6462, kb_relative_information_score: 76.4686, mean_absolute_error: 0.1583, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8399, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.3474, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3979, root_relative_squared_error: 0.8342, scimark_benchmark: 1318.1432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5121, kb_relative_information_score: 24.1074, mean_absolute_error: 0.35, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.4225, predictive_accuracy: 0.65, prior_entropy: 0.9362, recall: 0.65, relative_absolute_error: 0.768, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.5916, root_relative_squared_error: 1.2403, scimark_benchmark: 887.6719, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.794, f_measure: 0.8222, kappa: 0.6045, kb_relative_information_score: 71.9154, mean_absolute_error: 0.175, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8225, predictive_accuracy: 0.825, prior_entropy: 0.9362, recall: 0.825, relative_absolute_error: 0.384, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4183, root_relative_squared_error: 0.877, scimark_benchmark: 933.3136, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8996, f_measure: 0.8491, kappa: 0.6667, kb_relative_information_score: 68.1737, mean_absolute_error: 0.2005, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8488, predictive_accuracy: 0.85, prior_entropy: 0.9362, recall: 0.85, relative_absolute_error: 0.44, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3303, root_relative_squared_error: 0.6924, scimark_benchmark: 938.343, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8178, f_measure: 0.8402, kappa: 0.6462, kb_relative_information_score: 76.4686, mean_absolute_error: 0.1583, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8399, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.3474, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3979, root_relative_squared_error: 0.8342, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8271, f_measure: 0.8115, kappa: 0.5785, kb_relative_information_score: 22.3472, mean_absolute_error: 0.3881, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8146, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.8516, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4138, root_relative_squared_error: 0.8675, scimark_benchmark: 1324.8395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8694, f_measure: 0.8379, kappa: 0.6381, kb_relative_information_score: 58.1757, mean_absolute_error: 0.2448, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8406, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.537, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3611, root_relative_squared_error: 0.757, scimark_benchmark: 1319.6463, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8883, f_measure: 0.7905, kappa: 0.5294, kb_relative_information_score: 43.9323, mean_absolute_error: 0.3058, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 0.9362, recall: 0.8, relative_absolute_error: 0.671, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3645, root_relative_squared_error: 0.7643, scimark_benchmark: 1346.9602, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8017, f_measure: 0.7653, kappa: 0.4815, kb_relative_information_score: 48.4614, mean_absolute_error: 0.2669, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7644, predictive_accuracy: 0.7667, prior_entropy: 0.9362, recall: 0.7667, relative_absolute_error: 0.5856, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4057, root_relative_squared_error: 0.8506, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8342, f_measure: 0.8098, kappa: 0.5736, kb_relative_information_score: 52.3198, mean_absolute_error: 0.2555, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8162, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3842, root_relative_squared_error: 0.8054, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7967, f_measure: 0.7821, kappa: 0.5185, kb_relative_information_score: 52.432, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7813, predictive_accuracy: 0.7833, prior_entropy: 0.9362, recall: 0.7833, relative_absolute_error: 0.5647, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4264, root_relative_squared_error: 0.894, scimark_benchmark: 1376.7478, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7546, f_measure: 0.7689, kappa: 0.4982, kb_relative_information_score: 55.9794, mean_absolute_error: 0.2333, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7729, predictive_accuracy: 0.7667, prior_entropy: 0.9362, recall: 0.7667, relative_absolute_error: 0.512, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.483, root_relative_squared_error: 1.0127, scimark_benchmark: 1425.1294,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4661, f_measure: 0.5222, kappa: -0.0721, kb_relative_information_score: -5.488, mean_absolute_error: 0.4583, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.5106, predictive_accuracy: 0.5417, prior_entropy: 0.9362, recall: 0.5417, relative_absolute_error: 1.0057, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.677, root_relative_squared_error: 1.4194, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8839, f_measure: 0.8255, kappa: 0.6175, kb_relative_information_score: 71.8283, mean_absolute_error: 0.175, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8261, predictive_accuracy: 0.825, prior_entropy: 0.9362, recall: 0.825, relative_absolute_error: 0.3841, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3997, root_relative_squared_error: 0.838, scimark_benchmark: 902.4773, usercpu_time_millis: 7360, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 7350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7833, f_measure: 0.7427, kappa: 0.4212, kb_relative_information_score: 36.5286, mean_absolute_error: 0.3179, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7555, predictive_accuracy: 0.7583, prior_entropy: 0.9362, recall: 0.7583, relative_absolute_error: 0.6976, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4185, root_relative_squared_error: 0.8774, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7299, f_measure: 0.6976, kappa: 0.4042, kb_relative_information_score: 35.4903, mean_absolute_error: 0.3083, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7645, predictive_accuracy: 0.6917, prior_entropy: 0.9362, recall: 0.6917, relative_absolute_error: 0.6766, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.5553, root_relative_squared_error: 1.1642, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7711, f_measure: 0.8098, kappa: 0.5736, kb_relative_information_score: 69.6388, mean_absolute_error: 0.1833, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8162, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4023, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4282, root_relative_squared_error: 0.8977, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5815, f_measure: 0.6299, kappa: 0.1715, kb_relative_information_score: 21.8308, mean_absolute_error: 0.3583, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.6254, predictive_accuracy: 0.6417, prior_entropy: 0.9362, recall: 0.6417, relative_absolute_error: 0.7863, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.5986, root_relative_squared_error: 1.255, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4707, f_measure: 0.5121, kb_relative_information_score: -0.2247, mean_absolute_error: 0.4561, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.4225, predictive_accuracy: 0.65, prior_entropy: 0.9362, recall: 0.65, relative_absolute_error: 1.0007, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4772, root_relative_squared_error: 1.0006, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8602, f_measure: 0.8254, kappa: 0.6078, kb_relative_information_score: 60.9185, mean_absolute_error: 0.2283, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8378, predictive_accuracy: 0.8333, prior_entropy: 0.9362, recall: 0.8333, relative_absolute_error: 0.501, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3668, root_relative_squared_error: 0.7691, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8193, f_measure: 0.7833, kappa: 0.5238, kb_relative_information_score: 62.9071, mean_absolute_error: 0.2061, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7833, predictive_accuracy: 0.7833, prior_entropy: 0.9362, recall: 0.7833, relative_absolute_error: 0.4523, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4281, root_relative_squared_error: 0.8976, scimark_benchmark: 942.6953,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8446, f_measure: 0.7756, kappa: 0.5082, kb_relative_information_score: 62.8363, mean_absolute_error: 0.2062, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7763, predictive_accuracy: 0.775, prior_entropy: 0.9362, recall: 0.775, relative_absolute_error: 0.4524, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4183, root_relative_squared_error: 0.8771, scimark_benchmark: 926.6717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8446, f_measure: 0.7756, kappa: 0.5082, kb_relative_information_score: 62.8363, mean_absolute_error: 0.2062, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7763, predictive_accuracy: 0.775, prior_entropy: 0.9362, recall: 0.775, relative_absolute_error: 0.4524, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4183, root_relative_squared_error: 0.8771, scimark_benchmark: 936.7115,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9013, f_measure: 0.7867, kappa: 0.5238, kb_relative_information_score: 68.834, mean_absolute_error: 0.1845, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7876, predictive_accuracy: 0.7917, prior_entropy: 0.9362, recall: 0.7917, relative_absolute_error: 0.4049, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3762, root_relative_squared_error: 0.7887, scimark_benchmark: 894.7455, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9121, f_measure: 0.7693, kappa: 0.4824, kb_relative_information_score: 64.1985, mean_absolute_error: 0.2034, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8157, predictive_accuracy: 0.7917, prior_entropy: 0.9362, recall: 0.7917, relative_absolute_error: 0.4464, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3983, root_relative_squared_error: 0.8351, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8803, f_measure: 0.7658, kappa: 0.4759, kb_relative_information_score: 58.6744, mean_absolute_error: 0.2267, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8271, predictive_accuracy: 0.7917, prior_entropy: 0.9362, recall: 0.7917, relative_absolute_error: 0.4974, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4187, root_relative_squared_error: 0.8779, scimark_benchmark: 911.3823, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7962, f_measure: 0.6674, kappa: 0.2715, kb_relative_information_score: 47.4419, mean_absolute_error: 0.2671, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7774, predictive_accuracy: 0.725, prior_entropy: 0.9362, recall: 0.725, relative_absolute_error: 0.5862, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4714, root_relative_squared_error: 0.9884, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7955, f_measure: 0.6875, kappa: 0.3157, kb_relative_information_score: 45.0584, mean_absolute_error: 0.2795, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8151, predictive_accuracy: 0.7417, prior_entropy: 0.9362, recall: 0.7417, relative_absolute_error: 0.6132, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4736, root_relative_squared_error: 0.9929, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8649, f_measure: 0.801, kappa: 0.5652, kb_relative_information_score: 67.5931, mean_absolute_error: 0.1917, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8025, predictive_accuracy: 0.8, prior_entropy: 0.9362, recall: 0.8, relative_absolute_error: 0.4206, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.393, root_relative_squared_error: 0.824, scimark_benchmark: 945.6434, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8752, f_measure: 0.8167, kappa: 0.5971, kb_relative_information_score: 68.2939, mean_absolute_error: 0.1902, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8167, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4174, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3833, root_relative_squared_error: 0.8037, scimark_benchmark: 938.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8956, f_measure: 0.8167, kappa: 0.5971, kb_relative_information_score: 68.0501, mean_absolute_error: 0.1948, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8167, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4274, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3546, root_relative_squared_error: 0.7435, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8994, f_measure: 0.8412, kappa: 0.6501, kb_relative_information_score: 65.87, mean_absolute_error: 0.2107, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8409, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.4624, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3303, root_relative_squared_error: 0.6926, scimark_benchmark: 902.4773,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8979, f_measure: 0.8144, kappa: 0.588, kb_relative_information_score: 55.8677, mean_absolute_error: 0.2497, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8141, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.548, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3434, root_relative_squared_error: 0.7199, scimark_benchmark: 902.4773,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8506, build_cpu_time: 0.0019, build_memory: 819941360, f_measure: 0.801, kappa: 0.5652, kb_relative_information_score: 65.7244, mean_absolute_error: 0.1977, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8025, predictive_accuracy: 0.8, prior_entropy: 0.9362, recall: 0.8, relative_absolute_error: 0.4338, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4071, root_relative_squared_error: 0.8534, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8446, build_cpu_time: 0.0027, build_memory: 1183557784, f_measure: 0.7756, kappa: 0.5082, kb_relative_information_score: 62.8363, mean_absolute_error: 0.2062, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7763, predictive_accuracy: 0.775, prior_entropy: 0.9362, recall: 0.775, relative_absolute_error: 0.4524, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4183, root_relative_squared_error: 0.8771, scimark_benchmark: 943.2074,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8449, build_cpu_time: 0.133, build_memory: 534761635.2, f_measure: 0.7848, kappa: 0.5183, kb_relative_information_score: 64.1703, mean_absolute_error: 0.2033, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.7881, predictive_accuracy: 0.7917, prior_entropy: 0.9362, recall: 0.7917, relative_absolute_error: 0.4461, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4195, root_relative_squared_error: 0.8794, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8597, build_cpu_time: 0.2492, build_memory: 854897381.6, f_measure: 0.8193, kappa: 0.5954, kb_relative_information_score: 70.0644, mean_absolute_error: 0.1809, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8243, predictive_accuracy: 0.825, prior_entropy: 0.9362, recall: 0.825, relative_absolute_error: 0.397, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4074, root_relative_squared_error: 0.8542, scimark_benchmark: 939.0159,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8292, build_cpu_time: 1.019, build_memory: 51436232.8, f_measure: 0.8333, kappa: 0.6337, kb_relative_information_score: 74.3975, mean_absolute_error: 0.1662, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8333, predictive_accuracy: 0.8333, prior_entropy: 0.9362, recall: 0.8333, relative_absolute_error: 0.3647, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4012, root_relative_squared_error: 0.8412, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8001, build_cpu_time: 2.1871, build_memory: 45058712, f_measure: 0.8019, kappa: 0.5699, kb_relative_information_score: 65.1938, mean_absolute_error: 0.1993, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8056, predictive_accuracy: 0.8, prior_entropy: 0.9362, recall: 0.8, relative_absolute_error: 0.4374, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4418, root_relative_squared_error: 0.9263, scimark_benchmark: 919.0358,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8063, build_cpu_time: 10.0332, build_memory: 71232589.6, f_measure: 0.8176, kappa: 0.5906, kb_relative_information_score: 71.9692, mean_absolute_error: 0.1747, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8267, predictive_accuracy: 0.825, prior_entropy: 0.9362, recall: 0.825, relative_absolute_error: 0.3834, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4176, root_relative_squared_error: 0.8755, scimark_benchmark: 943.7751,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8825, build_cpu_time: 1.2681, build_memory: 136287194.4, f_measure: 0.8098, kappa: 0.5736, kb_relative_information_score: 68.9721, mean_absolute_error: 0.1859, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8162, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4078, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4142, root_relative_squared_error: 0.8685, scimark_benchmark: 937.9603,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8655, build_cpu_time: 0.4239, build_memory: 650107948.8, f_measure: 0.8412, kappa: 0.6501, kb_relative_information_score: 77.2093, mean_absolute_error: 0.1551, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8409, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.3404, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3794, root_relative_squared_error: 0.7954, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8443, build_cpu_time: 1.0893, build_memory: 1458512248.8, f_measure: 0.8412, kappa: 0.6501, kb_relative_information_score: 76.7861, mean_absolute_error: 0.1568, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8409, predictive_accuracy: 0.8417, prior_entropy: 0.9362, recall: 0.8417, relative_absolute_error: 0.344, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3943, root_relative_squared_error: 0.8267, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8378, build_cpu_time: 1.871, build_memory: 642751173.6, f_measure: 0.8491, kappa: 0.6667, kb_relative_information_score: 77.5236, mean_absolute_error: 0.1544, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8488, predictive_accuracy: 0.85, prior_entropy: 0.9362, recall: 0.85, relative_absolute_error: 0.3387, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3898, root_relative_squared_error: 0.8173, scimark_benchmark: 924.2473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.869, build_cpu_time: 0.0301, build_memory: 973913465.6, f_measure: 0.8079, kappa: 0.5686, kb_relative_information_score: 68.7126, mean_absolute_error: 0.1856, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8189, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4073, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4085, root_relative_squared_error: 0.8563, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.869, build_cpu_time: 0.044, build_memory: 1296567715.2, f_measure: 0.8079, kappa: 0.5686, kb_relative_information_score: 68.7126, mean_absolute_error: 0.1856, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8189, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4073, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4085, root_relative_squared_error: 0.8563, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.869, build_cpu_time: 0.026, build_memory: 1273509359.2, f_measure: 0.8079, kappa: 0.5686, kb_relative_information_score: 68.7126, mean_absolute_error: 0.1856, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8189, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4073, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4085, root_relative_squared_error: 0.8563, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8829, build_cpu_time: 0.0244, build_memory: 2009194304.8, f_measure: 0.8002, kappa: 0.5517, kb_relative_information_score: 68.1306, mean_absolute_error: 0.1883, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8081, predictive_accuracy: 0.8083, prior_entropy: 0.9362, recall: 0.8083, relative_absolute_error: 0.4131, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4129, root_relative_squared_error: 0.8656, scimark_benchmark: 906.6607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8924, build_cpu_time: 0.0175, build_memory: 827509938.4, f_measure: 0.8444, kappa: 0.6512, kb_relative_information_score: 72.0886, mean_absolute_error: 0.1783, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8528, predictive_accuracy: 0.85, prior_entropy: 0.9362, recall: 0.85, relative_absolute_error: 0.3913, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3715, root_relative_squared_error: 0.7788, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8759, build_cpu_time: 0.0039, build_memory: 247225636.8, f_measure: 0.8156, kappa: 0.5926, kb_relative_information_score: 68.7642, mean_absolute_error: 0.1889, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.815, predictive_accuracy: 0.8167, prior_entropy: 0.9362, recall: 0.8167, relative_absolute_error: 0.4145, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.3986, root_relative_squared_error: 0.8356, scimark_benchmark: 930.5854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8832, build_cpu_time: 0.0047, build_memory: 249311145.6, f_measure: 0.8019, kappa: 0.5699, kb_relative_information_score: 65.7972, mean_absolute_error: 0.1949, mean_prior_absolute_error: 0.4557, number_of_instances: 120, precision: 0.8056, predictive_accuracy: 0.8, prior_entropy: 0.9362, recall: 0.8, relative_absolute_error: 0.4277, root_mean_prior_squared_error: 0.477, root_mean_squared_error: 0.4149, root_relative_squared_error: 0.8698, scimark_benchmark: 936.1433,

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