Task
Supervised Classification on analcatdata_asbestos

Supervised Classification on analcatdata_asbestos

Task 3550 Supervised Classification analcatdata_asbestos 485 runs submitted
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  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_73 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 1332.9478,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8064, f_measure: 0.7356, kappa: 0.4719, kb_relative_information_score: 32.654, mean_absolute_error: 0.3092, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.744, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.6256, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4256, root_relative_squared_error: 0.8562, scimark_benchmark: 1346.4374,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8135, f_measure: 0.7815, kappa: 0.5564, kb_relative_information_score: 40.9641, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7835, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.5232, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8323, scimark_benchmark: 1313.5633, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7744, f_measure: 0.7235, kappa: 0.4494, kb_relative_information_score: 25.4103, mean_absolute_error: 0.3539, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7343, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.7161, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4398, root_relative_squared_error: 0.8849, scimark_benchmark: 1346.0226, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7741, f_measure: 0.759, kappa: 0.5123, kb_relative_information_score: 33.2923, mean_absolute_error: 0.3049, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.759, predictive_accuracy: 0.759, prior_entropy: 0.9919, recall: 0.759, relative_absolute_error: 0.6169, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4483, root_relative_squared_error: 0.902, scimark_benchmark: 1325.3966,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8088, f_measure: 0.7718, kappa: 0.5428, kb_relative_information_score: 31.1477, mean_absolute_error: 0.3242, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.778, predictive_accuracy: 0.7711, prior_entropy: 0.9919, recall: 0.7711, relative_absolute_error: 0.6559, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4182, root_relative_squared_error: 0.8413, scimark_benchmark: 1325.1654, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7103, f_measure: 0.7182, kappa: 0.4286, kb_relative_information_score: 36.2144, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7243, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.5264, root_relative_squared_error: 1.0591, scimark_benchmark: 1292.1745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 1328.1785,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 1349.9109,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 1329.1398,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8046, f_measure: 0.7477, kappa: 0.4946, kb_relative_information_score: 28.3247, mean_absolute_error: 0.3416, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7539, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.6911, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4263, root_relative_squared_error: 0.8577, scimark_benchmark: 1299.6719, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, f_measure: 0.7954, kappa: 0.5866, kb_relative_information_score: 33.862, mean_absolute_error: 0.3079, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7959, predictive_accuracy: 0.7952, prior_entropy: 0.9919, recall: 0.7952, relative_absolute_error: 0.6229, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.8121, scimark_benchmark: 1299.5896, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 1337.4384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8064, f_measure: 0.7356, kappa: 0.4719, kb_relative_information_score: 32.654, mean_absolute_error: 0.3092, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.744, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.6256, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4256, root_relative_squared_error: 0.8562, scimark_benchmark: 1335.2357,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7103, f_measure: 0.7182, kappa: 0.4286, kb_relative_information_score: 36.2144, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7243, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.5264, root_relative_squared_error: 1.0591, scimark_benchmark: 1340.5125, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8064, f_measure: 0.7356, kappa: 0.4719, kb_relative_information_score: 32.654, mean_absolute_error: 0.3092, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.744, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.6256, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4256, root_relative_squared_error: 0.8562, scimark_benchmark: 1333.202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8135, f_measure: 0.7815, kappa: 0.5564, kb_relative_information_score: 40.9641, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7835, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.5232, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8323, scimark_benchmark: 1253.0071, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7103, f_measure: 0.7182, kappa: 0.4286, kb_relative_information_score: 36.2144, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7243, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.5264, root_relative_squared_error: 1.0591, scimark_benchmark: 1274.7011, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, f_measure: 0.7954, kappa: 0.5866, kb_relative_information_score: 33.862, mean_absolute_error: 0.3079, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7959, predictive_accuracy: 0.7952, prior_entropy: 0.9919, recall: 0.7952, relative_absolute_error: 0.6229, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.8121, scimark_benchmark: 1354.3488, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8135, f_measure: 0.7815, kappa: 0.5564, kb_relative_information_score: 40.9641, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7835, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.5232, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8323, scimark_benchmark: 1278.6629,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.77, f_measure: 0.7473, kappa: 0.4893, kb_relative_information_score: 29.2871, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7478, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.672, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8824, scimark_benchmark: 932.5646,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, f_measure: 0.7954, kappa: 0.5866, kb_relative_information_score: 33.862, mean_absolute_error: 0.3079, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7959, predictive_accuracy: 0.7952, prior_entropy: 0.9919, recall: 0.7952, relative_absolute_error: 0.6229, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.8121, scimark_benchmark: 1347.5461, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7882, f_measure: 0.7477, kappa: 0.4946, kb_relative_information_score: 34.3923, mean_absolute_error: 0.2993, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7539, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.6056, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8604, scimark_benchmark: 918.0213,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7083, f_measure: 0.7357, kappa: 0.4692, kb_relative_information_score: 26.6632, mean_absolute_error: 0.3489, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7399, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.7059, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4557, root_relative_squared_error: 0.9169, scimark_benchmark: 1371.9645,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8135, f_measure: 0.7815, kappa: 0.5564, kb_relative_information_score: 40.9641, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7835, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.5232, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8323, scimark_benchmark: 1315.933, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7103, f_measure: 0.7182, kappa: 0.4286, kb_relative_information_score: 36.2144, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7243, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.5264, root_relative_squared_error: 1.0591, scimark_benchmark: 1354.3488, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7882, f_measure: 0.7477, kappa: 0.4946, kb_relative_information_score: 34.3923, mean_absolute_error: 0.2993, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7539, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.6056, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8604, scimark_benchmark: 1354.3488,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, f_measure: 0.7477, kappa: 0.492, kb_relative_information_score: 27.9634, mean_absolute_error: 0.3458, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7503, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.6996, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4065, root_relative_squared_error: 0.8178, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7779, f_measure: 0.7824, kappa: 0.5588, kb_relative_information_score: 46.378, mean_absolute_error: 0.2169, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7826, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.4388, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4657, root_relative_squared_error: 0.9369, scimark_benchmark: 929.0363, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7794, f_measure: 0.7717, kappa: 0.5404, kb_relative_information_score: 18.4726, mean_absolute_error: 0.4052, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7743, predictive_accuracy: 0.7711, prior_entropy: 0.9919, recall: 0.7711, relative_absolute_error: 0.8198, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4367, root_relative_squared_error: 0.8785, scimark_benchmark: 906.4475,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4445, f_measure: 0.3953, kb_relative_information_score: -0.1479, mean_absolute_error: 0.4948, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.3072, predictive_accuracy: 0.5542, prior_entropy: 0.9919, recall: 0.5542, relative_absolute_error: 1.0011, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4976, root_relative_squared_error: 1.0011, scimark_benchmark: 932.0242,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8296, f_measure: 0.7237, kappa: 0.4465, kb_relative_information_score: 28.6717, mean_absolute_error: 0.3401, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7297, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.6882, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4067, root_relative_squared_error: 0.8181, scimark_benchmark: 942.6843,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8046, f_measure: 0.7954, kappa: 0.5866, kb_relative_information_score: 34.7855, mean_absolute_error: 0.3003, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7959, predictive_accuracy: 0.7952, prior_entropy: 0.9919, recall: 0.7952, relative_absolute_error: 0.6077, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4173, root_relative_squared_error: 0.8394, scimark_benchmark: 937.1527, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8249, f_measure: 0.7714, kappa: 0.5379, kb_relative_information_score: 30.847, mean_absolute_error: 0.3268, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7718, predictive_accuracy: 0.7711, prior_entropy: 0.9919, recall: 0.7711, relative_absolute_error: 0.6612, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8223, scimark_benchmark: 929.0363,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8205, f_measure: 0.7595, kappa: 0.5149, kb_relative_information_score: 29.7347, mean_absolute_error: 0.3338, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7609, predictive_accuracy: 0.759, prior_entropy: 0.9919, recall: 0.759, relative_absolute_error: 0.6753, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4137, root_relative_squared_error: 0.8324, scimark_benchmark: 940.0008,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8046, f_measure: 0.7477, kappa: 0.4946, kb_relative_information_score: 28.3247, mean_absolute_error: 0.3416, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7539, predictive_accuracy: 0.747, prior_entropy: 0.9919, recall: 0.747, relative_absolute_error: 0.6911, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4263, root_relative_squared_error: 0.8577, scimark_benchmark: 938.0414, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7147, f_measure: 0.7236, kappa: 0.4436, kb_relative_information_score: 26.6015, mean_absolute_error: 0.3478, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7262, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.7038, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4651, root_relative_squared_error: 0.9357, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7941, f_measure: 0.7836, kappa: 0.5634, kb_relative_information_score: 36.5239, mean_absolute_error: 0.2865, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7849, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.5797, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4312, root_relative_squared_error: 0.8675, scimark_benchmark: 915.9693, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7929, f_measure: 0.7597, kappa: 0.5174, kb_relative_information_score: 34.7815, mean_absolute_error: 0.2973, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.764, predictive_accuracy: 0.759, prior_entropy: 0.9919, recall: 0.759, relative_absolute_error: 0.6016, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4267, root_relative_squared_error: 0.8584, scimark_benchmark: 935.5075, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7917, f_measure: 0.7357, kappa: 0.4692, kb_relative_information_score: 32.1096, mean_absolute_error: 0.312, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7399, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.6313, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4313, root_relative_squared_error: 0.8676, scimark_benchmark: 1336.2509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7879, f_measure: 0.7356, kappa: 0.4719, kb_relative_information_score: 30.7059, mean_absolute_error: 0.3215, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.744, predictive_accuracy: 0.7349, prior_entropy: 0.9919, recall: 0.7349, relative_absolute_error: 0.6505, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4312, root_relative_squared_error: 0.8675, scimark_benchmark: 937.1527, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7879, f_measure: 0.6994, kappa: 0.4015, kb_relative_information_score: 29.2365, mean_absolute_error: 0.3294, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.71, predictive_accuracy: 0.6988, prior_entropy: 0.9919, recall: 0.6988, relative_absolute_error: 0.6665, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4291, root_relative_squared_error: 0.8632, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7902, f_measure: 0.6996, kappa: 0.3952, kb_relative_information_score: 31.9294, mean_absolute_error: 0.3077, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7022, predictive_accuracy: 0.6988, prior_entropy: 0.9919, recall: 0.6988, relative_absolute_error: 0.6225, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4466, root_relative_squared_error: 0.8985, scimark_benchmark: 940.3347,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7923, f_measure: 0.7824, kappa: 0.5588, kb_relative_information_score: 33.9641, mean_absolute_error: 0.3039, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7826, predictive_accuracy: 0.7831, prior_entropy: 0.9919, recall: 0.7831, relative_absolute_error: 0.6149, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8823, scimark_benchmark: 869.6028,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6945, f_measure: 0.6987, kappa: 0.4095, kb_relative_information_score: 36.2144, mean_absolute_error: 0.2771, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.7714, predictive_accuracy: 0.7229, prior_entropy: 0.9919, recall: 0.7229, relative_absolute_error: 0.5607, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.5264, root_relative_squared_error: 1.0591, scimark_benchmark: 1363.454,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5053, f_measure: 0.4337, kappa: 0.0116, kb_relative_information_score: 7.7561, mean_absolute_error: 0.4458, mean_prior_absolute_error: 0.4943, number_of_instances: 83, precision: 0.5316, predictive_accuracy: 0.5542, prior_entropy: 0.9919, recall: 0.5542, relative_absolute_error: 0.9019, root_mean_prior_squared_error: 0.4971, root_mean_squared_error: 0.6677, root_relative_squared_error: 1.3433, scimark_benchmark: 887.6719,

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

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs