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OpenML
OpenML
Supervised Classification on analcatdata_gsssexsurvey

Supervised Classification on analcatdata_gsssexsurvey

Task 3717 Supervised Classification analcatdata_gsssexsurvey 506 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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506 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4987, f_measure: 0.6865, kappa: 0.0259, kb_relative_information_score: -28.3817, mean_absolute_error: 0.3383, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6666, predictive_accuracy: 0.717, prior_entropy: 0.7667, recall: 0.717, relative_absolute_error: 0.9797, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4745, root_relative_squared_error: 1.1453, scimark_benchmark: 942.9518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5351, f_measure: 0.7117, kappa: 0.0896, kb_relative_information_score: 29.2064, mean_absolute_error: 0.2453, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6971, predictive_accuracy: 0.7547, prior_entropy: 0.7667, recall: 0.7547, relative_absolute_error: 0.7104, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4953, root_relative_squared_error: 1.1953, scimark_benchmark: 930.5999, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6834, kb_relative_information_score: 42.3858, mean_absolute_error: 0.2201, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6082, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 0.6375, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4692, root_relative_squared_error: 1.1323, scimark_benchmark: 916.6405, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5124, f_measure: 0.6972, kappa: 0.0354, kb_relative_information_score: 35.7961, mean_absolute_error: 0.2327, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.685, predictive_accuracy: 0.7673, prior_entropy: 0.7667, recall: 0.7673, relative_absolute_error: 0.6739, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4824, root_relative_squared_error: 1.1642, scimark_benchmark: 1297.6599, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4509, f_measure: 0.7135, kappa: 0.0876, kb_relative_information_score: -21.9378, mean_absolute_error: 0.3669, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.7268, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 1.0626, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4318, root_relative_squared_error: 1.0422, scimark_benchmark: 1335.643, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4985, f_measure: 0.6822, kappa: -0.0038, kb_relative_information_score: 16.0271, mean_absolute_error: 0.2704, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6549, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 0.7832, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.52, root_relative_squared_error: 1.2551, scimark_benchmark: 935.5075, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.579, f_measure: 0.7017, kappa: 0.0509, kb_relative_information_score: -4.5734, mean_absolute_error: 0.3247, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6869, predictive_accuracy: 0.761, prior_entropy: 0.7667, recall: 0.761, relative_absolute_error: 0.9405, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4183, root_relative_squared_error: 1.0097, scimark_benchmark: 938.202, usercpu_time_millis: 260, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5479, f_measure: 0.7057, kappa: 0.0628, kb_relative_information_score: 3.2411, mean_absolute_error: 0.3203, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6972, predictive_accuracy: 0.7673, prior_entropy: 0.7667, recall: 0.7673, relative_absolute_error: 0.9277, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4094, root_relative_squared_error: 0.988, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5675, f_measure: 0.7017, kappa: 0.0509, kb_relative_information_score: 5.0727, mean_absolute_error: 0.3197, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6869, predictive_accuracy: 0.761, prior_entropy: 0.7667, recall: 0.761, relative_absolute_error: 0.926, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4101, root_relative_squared_error: 0.9897, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4798, f_measure: 0.6978, kappa: 0.0393, kb_relative_information_score: -4.6249, mean_absolute_error: 0.3278, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6784, predictive_accuracy: 0.7547, prior_entropy: 0.7667, recall: 0.7547, relative_absolute_error: 0.9494, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4359, root_relative_squared_error: 1.0521, scimark_benchmark: 1350.9691, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5457, f_measure: 0.7004, kappa: 0.0692, kb_relative_information_score: -24.9219, mean_absolute_error: 0.3464, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6832, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 1.0033, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4469, root_relative_squared_error: 1.0786, scimark_benchmark: 1336.2509, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5277, f_measure: 0.673, kappa: 0.0475, kb_relative_information_score: -15.1471, mean_absolute_error: 0.3302, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.673, predictive_accuracy: 0.673, prior_entropy: 0.7667, recall: 0.673, relative_absolute_error: 0.9563, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.57, root_relative_squared_error: 1.3757, scimark_benchmark: 1316.0472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5045, f_measure: 0.6803, kappa: -0.0124, kb_relative_information_score: 0.4666, mean_absolute_error: 0.3413, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6071, predictive_accuracy: 0.7736, prior_entropy: 0.7667, recall: 0.7736, relative_absolute_error: 0.9886, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4181, root_relative_squared_error: 1.0091, scimark_benchmark: 1320.2556,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4591, f_measure: 0.6803, kappa: -0.0124, kb_relative_information_score: -0.4916, mean_absolute_error: 0.3438, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6071, predictive_accuracy: 0.7736, prior_entropy: 0.7667, recall: 0.7736, relative_absolute_error: 0.9956, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4189, root_relative_squared_error: 1.0109, scimark_benchmark: 1354.2491, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.493, f_measure: 0.6615, kappa: -0.015, kb_relative_information_score: -13.6265, mean_absolute_error: 0.327, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6514, predictive_accuracy: 0.673, prior_entropy: 0.7667, recall: 0.673, relative_absolute_error: 0.9472, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5719, root_relative_squared_error: 1.3802, scimark_benchmark: 1325.942, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.519, f_measure: 0.6949, kappa: 0.046, kb_relative_information_score: 16.0271, mean_absolute_error: 0.2704, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6751, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 0.7832, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.52, root_relative_squared_error: 1.2551, scimark_benchmark: 1290.1085, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6108, f_measure: 0.7493, kappa: 0.2417, kb_relative_information_score: 12.3334, mean_absolute_error: 0.2939, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.7418, predictive_accuracy: 0.761, prior_entropy: 0.7667, recall: 0.761, relative_absolute_error: 0.851, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4446, root_relative_squared_error: 1.073, scimark_benchmark: 1465.2979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5308, f_measure: 0.7135, kappa: 0.0876, kb_relative_information_score: 42.3858, mean_absolute_error: 0.2201, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.7268, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 0.6375, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4692, root_relative_squared_error: 1.1323, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4919, f_measure: 0.6772, kappa: -0.0244, kb_relative_information_score: 35.7961, mean_absolute_error: 0.2327, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.606, predictive_accuracy: 0.7673, prior_entropy: 0.7667, recall: 0.7673, relative_absolute_error: 0.6739, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4824, root_relative_squared_error: 1.1642, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4548, f_measure: 0.6834, kb_relative_information_score: -1.2299, mean_absolute_error: 0.3457, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6082, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 1.0012, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4146, root_relative_squared_error: 1.0006, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5185, f_measure: 0.6898, kappa: 0.0121, kb_relative_information_score: -4.956, mean_absolute_error: 0.347, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6645, predictive_accuracy: 0.7547, prior_entropy: 0.7667, recall: 0.7547, relative_absolute_error: 1.005, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4392, root_relative_squared_error: 1.0601, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4876, f_measure: 0.6861, kappa: 0.0065, kb_relative_information_score: 12.0369, mean_absolute_error: 0.2833, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6597, predictive_accuracy: 0.7358, prior_entropy: 0.7667, recall: 0.7358, relative_absolute_error: 0.8205, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4928, root_relative_squared_error: 1.1892, 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: 0.5056, f_measure: 0.69, kappa: 0.0172, kb_relative_information_score: -23.5468, mean_absolute_error: 0.354, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6651, predictive_accuracy: 0.7421, prior_entropy: 0.7667, recall: 0.7421, relative_absolute_error: 1.0253, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4498, root_relative_squared_error: 1.0854, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5056, f_measure: 0.69, kappa: 0.0172, kb_relative_information_score: -23.5468, mean_absolute_error: 0.354, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6651, predictive_accuracy: 0.7421, prior_entropy: 0.7667, recall: 0.7421, relative_absolute_error: 1.0253, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4498, root_relative_squared_error: 1.0854, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5056, f_measure: 0.69, kappa: 0.0172, kb_relative_information_score: -23.5468, mean_absolute_error: 0.354, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6651, predictive_accuracy: 0.7421, prior_entropy: 0.7667, recall: 0.7421, relative_absolute_error: 1.0253, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4498, root_relative_squared_error: 1.0854, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5423, f_measure: 0.7046, kappa: 0.0601, kb_relative_information_score: 40.8758, mean_absolute_error: 0.2251, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.7239, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 0.6518, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.459, root_relative_squared_error: 1.1078, scimark_benchmark: 936.6206, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.535, f_measure: 0.7083, kappa: 0.073, kb_relative_information_score: 41.1524, mean_absolute_error: 0.2254, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.7617, predictive_accuracy: 0.7862, prior_entropy: 0.7667, recall: 0.7862, relative_absolute_error: 0.6529, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4583, root_relative_squared_error: 1.106, scimark_benchmark: 936.6206, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5209, f_measure: 0.6803, kappa: -0.0124, kb_relative_information_score: 37.043, mean_absolute_error: 0.2303, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6071, predictive_accuracy: 0.7736, prior_entropy: 0.7667, recall: 0.7736, relative_absolute_error: 0.667, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4643, root_relative_squared_error: 1.1205, scimark_benchmark: 938.2848, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5035, f_measure: 0.6834, kb_relative_information_score: 36.26, mean_absolute_error: 0.2322, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6082, predictive_accuracy: 0.7799, prior_entropy: 0.7667, recall: 0.7799, relative_absolute_error: 0.6724, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4678, root_relative_squared_error: 1.129, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5101, f_measure: 0.6803, kappa: -0.0124, kb_relative_information_score: 37.2246, mean_absolute_error: 0.2309, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6071, predictive_accuracy: 0.7736, prior_entropy: 0.7667, recall: 0.7736, relative_absolute_error: 0.6686, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4691, root_relative_squared_error: 1.1322, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5138, f_measure: 0.6654, kappa: -0.0205, kb_relative_information_score: -18.9366, mean_absolute_error: 0.3356, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6493, predictive_accuracy: 0.6855, prior_entropy: 0.7667, recall: 0.6855, relative_absolute_error: 0.972, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4842, root_relative_squared_error: 1.1685, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5327, f_measure: 0.6807, kappa: 0.0017, kb_relative_information_score: -15.7379, mean_absolute_error: 0.3334, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6573, predictive_accuracy: 0.717, prior_entropy: 0.7667, recall: 0.717, relative_absolute_error: 0.9654, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4672, root_relative_squared_error: 1.1275, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5551, f_measure: 0.6847, kappa: 0.0116, kb_relative_information_score: -14.6631, mean_absolute_error: 0.3331, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6614, predictive_accuracy: 0.7233, prior_entropy: 0.7667, recall: 0.7233, relative_absolute_error: 0.9646, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4553, root_relative_squared_error: 1.0988, scimark_benchmark: 924.6116,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5662, f_measure: 0.6888, kappa: 0.0217, kb_relative_information_score: -9.3213, mean_absolute_error: 0.3305, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6658, predictive_accuracy: 0.7296, prior_entropy: 0.7667, recall: 0.7296, relative_absolute_error: 0.9572, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4462, root_relative_squared_error: 1.077, scimark_benchmark: 947.9494, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5056, build_cpu_time: 0.0045, build_memory: 1778369791.4969, f_measure: 0.69, kappa: 0.0172, kb_relative_information_score: -23.5468, mean_absolute_error: 0.354, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6651, predictive_accuracy: 0.7421, prior_entropy: 0.7667, recall: 0.7421, relative_absolute_error: 1.0253, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4498, root_relative_squared_error: 1.0854, scimark_benchmark: 943.5504,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.518, build_cpu_time: 2.3717, build_memory: 35437319.4969, f_measure: 0.692, kappa: 0.0725, kb_relative_information_score: -5.1742, mean_absolute_error: 0.3108, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.682, predictive_accuracy: 0.7044, prior_entropy: 0.7667, recall: 0.7044, relative_absolute_error: 0.9001, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5162, root_relative_squared_error: 1.2459, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5518, build_cpu_time: 4.4845, build_memory: 681739535.5975, f_measure: 0.6822, kappa: 0.0649, kb_relative_information_score: -6.4892, mean_absolute_error: 0.3115, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.679, predictive_accuracy: 0.6855, prior_entropy: 0.7667, recall: 0.6855, relative_absolute_error: 0.9022, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5316, root_relative_squared_error: 1.2829, scimark_benchmark: 909.5718,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5279, build_cpu_time: 4.7583, build_memory: 130981162.6164, f_measure: 0.6683, kappa: 0.039, kb_relative_information_score: -15.7318, mean_absolute_error: 0.3303, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6701, predictive_accuracy: 0.6667, prior_entropy: 0.7667, recall: 0.6667, relative_absolute_error: 0.9567, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5698, root_relative_squared_error: 1.3751, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5433, build_cpu_time: 2.7824, build_memory: 550367196.3774, f_measure: 0.6776, kappa: 0.0561, kb_relative_information_score: -10.1917, mean_absolute_error: 0.3205, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6759, predictive_accuracy: 0.6792, prior_entropy: 0.7667, recall: 0.6792, relative_absolute_error: 0.9282, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5503, root_relative_squared_error: 1.3282, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5253, build_cpu_time: 1.6685, build_memory: 158828268.478, f_measure: 0.6433, kappa: -0.0335, kb_relative_information_score: -28.3881, mean_absolute_error: 0.3512, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6451, predictive_accuracy: 0.6415, prior_entropy: 0.7667, recall: 0.6415, relative_absolute_error: 1.0172, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5628, root_relative_squared_error: 1.3582, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6161, build_cpu_time: 0.0764, build_memory: 372171550.9434, f_measure: 0.6874, kappa: 0.0391, kb_relative_information_score: 2.4601, mean_absolute_error: 0.2939, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.671, predictive_accuracy: 0.7107, prior_entropy: 0.7667, recall: 0.7107, relative_absolute_error: 0.8512, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4853, root_relative_squared_error: 1.1713, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6085, build_cpu_time: 0.1727, build_memory: 213785166.1887, f_measure: 0.7056, kappa: 0.1019, kb_relative_information_score: 6.6778, mean_absolute_error: 0.2905, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6932, predictive_accuracy: 0.7233, prior_entropy: 0.7667, recall: 0.7233, relative_absolute_error: 0.8414, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5064, root_relative_squared_error: 1.2221, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5702, build_cpu_time: 0.345, build_memory: 91559677.283, f_measure: 0.6745, kappa: 0.0112, kb_relative_information_score: -1.7697, mean_absolute_error: 0.3041, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6606, predictive_accuracy: 0.6918, prior_entropy: 0.7667, recall: 0.6918, relative_absolute_error: 0.8806, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5301, root_relative_squared_error: 1.2794, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5342, build_cpu_time: 0.5948, build_memory: 832791063.5472, f_measure: 0.6875, kappa: 0.0631, kb_relative_information_score: -0.47, mean_absolute_error: 0.3021, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6786, predictive_accuracy: 0.6981, prior_entropy: 0.7667, recall: 0.6981, relative_absolute_error: 0.8748, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5403, root_relative_squared_error: 1.3039, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.535, build_cpu_time: 1.5503, build_memory: 1684442375.8491, f_measure: 0.6785, kappa: 0.0449, kb_relative_information_score: -6.5179, mean_absolute_error: 0.3132, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6722, predictive_accuracy: 0.6855, prior_entropy: 0.7667, recall: 0.6855, relative_absolute_error: 0.9072, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.5536, root_relative_squared_error: 1.336, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5779, build_cpu_time: 0.0254, build_memory: 894069468.0755, f_measure: 0.6939, kappa: 0.0281, kb_relative_information_score: -3.3239, mean_absolute_error: 0.3134, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6713, predictive_accuracy: 0.7484, prior_entropy: 0.7667, recall: 0.7484, relative_absolute_error: 0.9076, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4394, root_relative_squared_error: 1.0604, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5779, build_cpu_time: 0.0228, build_memory: 706789657.8616, f_measure: 0.6939, kappa: 0.0281, kb_relative_information_score: -3.3239, mean_absolute_error: 0.3134, mean_prior_absolute_error: 0.3453, number_of_instances: 159, precision: 0.6713, predictive_accuracy: 0.7484, prior_entropy: 0.7667, recall: 0.7484, relative_absolute_error: 0.9076, root_mean_prior_squared_error: 0.4143, root_mean_squared_error: 0.4394, root_relative_squared_error: 1.0604, scimark_benchmark: 930.5854,

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