OpenML
Supervised Classification on banana

Supervised Classification on banana

Task 10091 Supervised Classification banana 132 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5182, f_measure: 0.475, kappa: 0.0392, kb_relative_information_score: 549.0507, mean_absolute_error: 0.4413, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5488, predictive_accuracy: 0.5587, prior_entropy: 0.9923, recall: 0.5587, relative_absolute_error: 0.8922, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6643, root_relative_squared_error: 1.3358, usercpu_time_millis: 0.097, usercpu_time_millis_testing: 0.011, usercpu_time_millis_training: 0.086,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9019, f_measure: 0.906, kappa: 0.8095, kb_relative_information_score: 4292.5061, mean_absolute_error: 0.0936, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.9077, predictive_accuracy: 0.9064, prior_entropy: 0.9923, recall: 0.9064, relative_absolute_error: 0.1892, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3059, root_relative_squared_error: 0.6151, usercpu_time_millis: 7.511, usercpu_time_millis_testing: 1.914, usercpu_time_millis_training: 5.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5178, f_measure: 0.4745, kappa: 0.0384, kb_relative_information_score: 544.9883, mean_absolute_error: 0.4417, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5479, predictive_accuracy: 0.5583, prior_entropy: 0.9923, recall: 0.5583, relative_absolute_error: 0.8929, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6646, root_relative_squared_error: 1.3364, usercpu_time_millis: 0.362, usercpu_time_millis_testing: 0.045, usercpu_time_millis_training: 0.317,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8822, f_measure: 0.8875, kappa: 0.772, kb_relative_information_score: 4097.5133, mean_absolute_error: 0.1117, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8907, predictive_accuracy: 0.8883, prior_entropy: 0.9923, recall: 0.8883, relative_absolute_error: 0.2258, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3342, root_relative_squared_error: 0.672, usercpu_time_millis: 5.502, usercpu_time_millis_testing: 0.364, usercpu_time_millis_training: 5.138,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8838, f_measure: 0.8861, kappa: 0.7694, kb_relative_information_score: 4075.1703, mean_absolute_error: 0.1138, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8862, predictive_accuracy: 0.8862, prior_entropy: 0.9923, recall: 0.8862, relative_absolute_error: 0.23, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3373, root_relative_squared_error: 0.6782, usercpu_time_millis: 0.764, usercpu_time_millis_testing: 0.716, usercpu_time_millis_training: 0.048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8825, f_measure: 0.8873, kappa: 0.7715, kb_relative_information_score: 4093.4509, mean_absolute_error: 0.1121, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8896, predictive_accuracy: 0.8879, prior_entropy: 0.9923, recall: 0.8879, relative_absolute_error: 0.2266, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3348, root_relative_squared_error: 0.6732, usercpu_time_millis: 2.136, usercpu_time_millis_testing: 0.556, usercpu_time_millis_training: 1.58,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8673, f_measure: 0.8687, kappa: 0.7345, kb_relative_information_score: 3886.2711, mean_absolute_error: 0.1313, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8687, predictive_accuracy: 0.8687, prior_entropy: 0.9923, recall: 0.8687, relative_absolute_error: 0.2655, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.7287, usercpu_time_millis: 21.052, usercpu_time_millis_testing: 2.327, usercpu_time_millis_training: 18.725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5182, f_measure: 0.4752, kappa: 0.0393, kb_relative_information_score: 549.0507, mean_absolute_error: 0.4413, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5487, predictive_accuracy: 0.5587, prior_entropy: 0.9923, recall: 0.5587, relative_absolute_error: 0.8922, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6643, root_relative_squared_error: 1.3358, usercpu_time_millis: 13.944, usercpu_time_millis_testing: 3.404, usercpu_time_millis_training: 10.54,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5182, f_measure: 0.4748, kappa: 0.0391, kb_relative_information_score: 549.0507, mean_absolute_error: 0.4413, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5488, predictive_accuracy: 0.5587, prior_entropy: 0.9923, recall: 0.5587, relative_absolute_error: 0.8922, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6643, root_relative_squared_error: 1.3358, usercpu_time_millis: 5.344, usercpu_time_millis_testing: 0.043, usercpu_time_millis_training: 5.301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5203, f_measure: 0.4334, kappa: 0.0445, kb_relative_information_score: 666.8588, mean_absolute_error: 0.4304, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7295, predictive_accuracy: 0.5696, prior_entropy: 0.9923, recall: 0.5696, relative_absolute_error: 0.8701, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.656, root_relative_squared_error: 1.3191, usercpu_time_millis: 0.645, usercpu_time_millis_testing: 0.15, usercpu_time_millis_training: 0.495,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8954, f_measure: 0.8979, kappa: 0.7933, kb_relative_information_score: 4203.1344, mean_absolute_error: 0.1019, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8982, predictive_accuracy: 0.8981, prior_entropy: 0.9923, recall: 0.8981, relative_absolute_error: 0.206, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3192, root_relative_squared_error: 0.6418, usercpu_time_millis: 382.546, usercpu_time_millis_testing: 3.84, usercpu_time_millis_training: 378.706,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3923, kb_relative_information_score: 473.8972, mean_absolute_error: 0.4483, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.3044, predictive_accuracy: 0.5517, prior_entropy: 0.9923, recall: 0.5517, relative_absolute_error: 0.9063, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6696, root_relative_squared_error: 1.3463, usercpu_time_millis: 1.855, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5294, f_measure: 0.5326, kappa: 0.0606, kb_relative_information_score: 443.4296, mean_absolute_error: 0.4511, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5381, predictive_accuracy: 0.5489, prior_entropy: 0.9923, recall: 0.5489, relative_absolute_error: 0.912, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6717, root_relative_squared_error: 1.3506, usercpu_time_millis: 2.006, usercpu_time_millis_testing: 0.021, usercpu_time_millis_training: 1.985,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8985, f_measure: 0.9013, kappa: 0.8001, kb_relative_information_score: 4239.6955, mean_absolute_error: 0.0985, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.9017, predictive_accuracy: 0.9015, prior_entropy: 0.9923, recall: 0.9015, relative_absolute_error: 0.1991, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3138, root_relative_squared_error: 0.631, usercpu_time_millis: 54.851, usercpu_time_millis_testing: 1.504, usercpu_time_millis_training: 53.347,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7779, f_measure: 0.786, kappa: 0.5671, kb_relative_information_score: 3041.3023, mean_absolute_error: 0.2098, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7974, predictive_accuracy: 0.7902, prior_entropy: 0.9923, recall: 0.7902, relative_absolute_error: 0.4242, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4581, root_relative_squared_error: 0.921, usercpu_time_millis: 2.133, usercpu_time_millis_testing: 0.08, usercpu_time_millis_training: 2.053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8477, f_measure: 0.8545, kappa: 0.7052, kb_relative_information_score: 3752.2135, mean_absolute_error: 0.1438, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8609, predictive_accuracy: 0.8562, prior_entropy: 0.9923, recall: 0.8562, relative_absolute_error: 0.2907, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3792, root_relative_squared_error: 0.7624, usercpu_time_millis: 8.624, usercpu_time_millis_testing: 0.23, usercpu_time_millis_training: 8.394,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8299, f_measure: 0.8379, kappa: 0.6718, kb_relative_information_score: 3583.626, mean_absolute_error: 0.1594, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8484, predictive_accuracy: 0.8406, prior_entropy: 0.9923, recall: 0.8406, relative_absolute_error: 0.3223, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3993, root_relative_squared_error: 0.8029, usercpu_time_millis: 22.559, usercpu_time_millis_testing: 0.109, usercpu_time_millis_training: 22.45,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8813, f_measure: 0.8846, kappa: 0.7662, kb_relative_information_score: 4060.9521, mean_absolute_error: 0.1151, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8851, predictive_accuracy: 0.8849, prior_entropy: 0.9923, recall: 0.8849, relative_absolute_error: 0.2327, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3393, root_relative_squared_error: 0.6822, usercpu_time_millis: 9.199, usercpu_time_millis_testing: 0.306, usercpu_time_millis_training: 8.893,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.518, f_measure: 0.4747, kappa: 0.0387, kb_relative_information_score: 547.0195, mean_absolute_error: 0.4415, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5483, predictive_accuracy: 0.5585, prior_entropy: 0.9923, recall: 0.5585, relative_absolute_error: 0.8926, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.6645, root_relative_squared_error: 1.3361, usercpu_time_millis: 0.661, usercpu_time_millis_testing: 0.03, usercpu_time_millis_training: 0.631,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9238, f_measure: 0.8566, kappa: 0.7095, kb_relative_information_score: 3181.8433, mean_absolute_error: 0.2094, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8582, predictive_accuracy: 0.8574, prior_entropy: 0.9923, recall: 0.8574, relative_absolute_error: 0.4233, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3271, root_relative_squared_error: 0.6577, scimark_benchmark: 1167.8052, usercpu_time_millis: 730, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 720,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.968, f_measure: 0.9037, kappa: 0.8051, kb_relative_information_score: 3939.3575, mean_absolute_error: 0.1349, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.9042, predictive_accuracy: 0.904, prior_entropy: 0.9923, recall: 0.904, relative_absolute_error: 0.2726, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.2646, root_relative_squared_error: 0.532, scimark_benchmark: 1240.9521, usercpu_time_millis: 17580, usercpu_time_millis_testing: 920, usercpu_time_millis_training: 16660,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9587, f_measure: 0.8854, kappa: 0.768, kb_relative_information_score: 3787.3596, mean_absolute_error: 0.1471, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8857, predictive_accuracy: 0.8857, prior_entropy: 0.9923, recall: 0.8857, relative_absolute_error: 0.2973, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.2806, root_relative_squared_error: 0.5643, scimark_benchmark: 1199.1754, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.795, f_measure: 0.7193, kappa: 0.4315, kb_relative_information_score: 1432.5338, mean_absolute_error: 0.3764, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7245, predictive_accuracy: 0.7234, prior_entropy: 0.9923, recall: 0.7234, relative_absolute_error: 0.7609, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4284, root_relative_squared_error: 0.8615, scimark_benchmark: 1238.0575, usercpu_time_millis: 670, usercpu_time_millis_testing: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7449, f_measure: 0.7114, kappa: 0.4309, kb_relative_information_score: 1563.701, mean_absolute_error: 0.3598, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7699, predictive_accuracy: 0.7308, prior_entropy: 0.9923, recall: 0.7308, relative_absolute_error: 0.7273, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4325, root_relative_squared_error: 0.8697, scimark_benchmark: 1237.8253, usercpu_time_millis: 1830, usercpu_time_millis_training: 1830,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8676, f_measure: 0.8687, kappa: 0.7345, kb_relative_information_score: 3884.0573, mean_absolute_error: 0.1316, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8687, predictive_accuracy: 0.8687, prior_entropy: 0.9923, recall: 0.8687, relative_absolute_error: 0.266, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.3624, root_relative_squared_error: 0.7286, scimark_benchmark: 473.1656, usercpu_time_millis: 4330, usercpu_time_millis_testing: 4320, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9369, f_measure: 0.8873, kappa: 0.7715, kb_relative_information_score: 3738.2507, mean_absolute_error: 0.1543, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.8896, predictive_accuracy: 0.8879, prior_entropy: 0.9923, recall: 0.8879, relative_absolute_error: 0.3118, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.2954, root_relative_squared_error: 0.5939, scimark_benchmark: 473.1656, usercpu_time_millis: 200, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.547, f_measure: 0.4747, kappa: 0.0387, kb_relative_information_score: 40.3992, mean_absolute_error: 0.4914, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.5483, predictive_accuracy: 0.5585, prior_entropy: 0.9923, recall: 0.5585, relative_absolute_error: 0.9933, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9969, scimark_benchmark: 1254.1389, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7368, f_measure: 0.6535, kappa: 0.3238, kb_relative_information_score: 1065.5642, mean_absolute_error: 0.4061, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7184, predictive_accuracy: 0.6819, prior_entropy: 0.9923, recall: 0.6819, relative_absolute_error: 0.821, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4696, root_relative_squared_error: 0.9442, scimark_benchmark: 473.1656, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5989, f_measure: 0.5751, kappa: 0.2001, kb_relative_information_score: 318.6128, mean_absolute_error: 0.4694, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.6264, predictive_accuracy: 0.586, prior_entropy: 0.9923, recall: 0.586, relative_absolute_error: 0.949, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4851, root_relative_squared_error: 0.9754, scimark_benchmark: 479.2609, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.663, f_measure: 0.5814, kappa: 0.1809, kb_relative_information_score: 294.7513, mean_absolute_error: 0.473, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.6222, predictive_accuracy: 0.6142, prior_entropy: 0.9923, recall: 0.6142, relative_absolute_error: 0.9562, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4837, root_relative_squared_error: 0.9726, scimark_benchmark: 1230.3004, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7763, f_measure: 0.714, kappa: 0.4217, kb_relative_information_score: 1408.2339, mean_absolute_error: 0.3785, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.7229, predictive_accuracy: 0.7198, prior_entropy: 0.9923, recall: 0.7198, relative_absolute_error: 0.7651, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4338, root_relative_squared_error: 0.8723, scimark_benchmark: 1241.5236, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.663, f_measure: 0.5814, kappa: 0.1809, kb_relative_information_score: 294.7513, mean_absolute_error: 0.473, mean_prior_absolute_error: 0.4947, number_of_instances: 5300, precision: 0.6222, predictive_accuracy: 0.6142, prior_entropy: 0.9923, recall: 0.6142, relative_absolute_error: 0.9562, root_mean_prior_squared_error: 0.4973, root_mean_squared_error: 0.4837, root_relative_squared_error: 0.9726, scimark_benchmark: 1248.2165,

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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)

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