Task
Supervised Classification on dermatology

Supervised Classification on dermatology

Task 1799 Supervised Classification dermatology 306 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6181, build_cpu_time: 0.0009, build_memory: 668441732.8, f_measure: 0.3647, kappa: 0.2299, kb_relative_information_score: 520.6466, mean_absolute_error: 0.1967, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3697, predictive_accuracy: 0.4098, prior_entropy: 2.4378, recall: 0.4098, relative_absolute_error: 0.7383, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4435, root_relative_squared_error: 1.2156, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6181, build_cpu_time: 0.001, build_memory: 1108464154.4, f_measure: 0.3647, kappa: 0.2299, kb_relative_information_score: 520.6466, mean_absolute_error: 0.1967, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3697, predictive_accuracy: 0.4098, prior_entropy: 2.4378, recall: 0.4098, relative_absolute_error: 0.7383, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4435, root_relative_squared_error: 1.2156, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6181, build_cpu_time: 0.0042, build_memory: 224919994.4, f_measure: 0.3647, kappa: 0.2299, kb_relative_information_score: 520.6466, mean_absolute_error: 0.1967, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3697, predictive_accuracy: 0.4098, prior_entropy: 2.4378, recall: 0.4098, relative_absolute_error: 0.7383, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4435, root_relative_squared_error: 1.2156, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.998, build_cpu_time: 0.0386, build_memory: 470013612, f_measure: 0.9643, kappa: 0.9554, kb_relative_information_score: 1546.6163, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9644, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.2478, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1359, root_relative_squared_error: 0.3726, scimark_benchmark: 942.3945,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9789, build_cpu_time: 0.1417, build_memory: 267449672, f_measure: 0.9466, kappa: 0.9323, kb_relative_information_score: 1706.6056, mean_absolute_error: 0.0182, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9482, predictive_accuracy: 0.9459, prior_entropy: 2.4378, recall: 0.9459, relative_absolute_error: 0.0683, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1287, root_relative_squared_error: 0.3527, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6181, build_cpu_time: 0.001, build_memory: 307852180.8, f_measure: 0.3647, kappa: 0.2299, kb_relative_information_score: 520.6466, mean_absolute_error: 0.1967, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3697, predictive_accuracy: 0.4098, prior_entropy: 2.4378, recall: 0.4098, relative_absolute_error: 0.7383, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4435, root_relative_squared_error: 1.2156, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9744, build_cpu_time: 0.2477, build_memory: 717614611.2, f_measure: 0.9439, kappa: 0.9289, kb_relative_information_score: 1698.9588, mean_absolute_error: 0.0192, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9454, predictive_accuracy: 0.9432, prior_entropy: 2.4378, recall: 0.9432, relative_absolute_error: 0.0722, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1336, root_relative_squared_error: 0.3662, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9872, build_cpu_time: 0.0644, build_memory: 725262752.8, f_measure: 0.9515, kappa: 0.9384, kb_relative_information_score: 1717.1856, mean_absolute_error: 0.0165, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.953, predictive_accuracy: 0.9508, prior_entropy: 2.4378, recall: 0.9508, relative_absolute_error: 0.0618, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1205, root_relative_squared_error: 0.3302, scimark_benchmark: 943.2074,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9959, build_cpu_time: 0.0589, build_memory: 875609676.8, f_measure: 0.9599, kappa: 0.9499, kb_relative_information_score: 1672.7994, mean_absolute_error: 0.0343, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9609, predictive_accuracy: 0.9601, prior_entropy: 2.4378, recall: 0.9601, relative_absolute_error: 0.1285, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1112, root_relative_squared_error: 0.3048, scimark_benchmark: 925.3536,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9872, f_measure: 0.9388, kappa: 0.9228, kb_relative_information_score: 1690.3798, mean_absolute_error: 0.0221, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9399, predictive_accuracy: 0.9383, prior_entropy: 2.4378, recall: 0.9383, relative_absolute_error: 0.083, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1346, root_relative_squared_error: 0.3688, scimark_benchmark: 1066.7184, usercpu_time_millis: 2720, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 2670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9726, f_measure: 0.9294, kappa: 0.9116, kb_relative_information_score: 1649.7466, mean_absolute_error: 0.0298, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9303, predictive_accuracy: 0.9295, prior_entropy: 2.4378, recall: 0.9295, relative_absolute_error: 0.1119, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1459, root_relative_squared_error: 0.3999, scimark_benchmark: 939.9176, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7951, f_measure: 0.3594, kappa: 0.335, kb_relative_information_score: 649.0318, mean_absolute_error: 0.1953, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3012, predictive_accuracy: 0.4934, prior_entropy: 2.4378, recall: 0.4934, relative_absolute_error: 0.7331, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3147, root_relative_squared_error: 0.8625, scimark_benchmark: 935.5075,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7951, f_measure: 0.3594, kappa: 0.335, kb_relative_information_score: 649.0318, mean_absolute_error: 0.1953, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3012, predictive_accuracy: 0.4934, prior_entropy: 2.4378, recall: 0.4934, relative_absolute_error: 0.7331, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3147, root_relative_squared_error: 0.8625, scimark_benchmark: 854.5188, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7951, f_measure: 0.3594, kappa: 0.335, kb_relative_information_score: 649.0318, mean_absolute_error: 0.1953, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3012, predictive_accuracy: 0.4934, prior_entropy: 2.4378, recall: 0.4934, relative_absolute_error: 0.7331, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3147, root_relative_squared_error: 0.8625, scimark_benchmark: 915.6729, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9599, f_measure: 0.8877, kappa: 0.8584, kb_relative_information_score: 1538.5539, mean_absolute_error: 0.0496, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.8906, predictive_accuracy: 0.8874, prior_entropy: 2.4378, recall: 0.8874, relative_absolute_error: 0.1861, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1762, root_relative_squared_error: 0.4829, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5445, f_measure: 0.2537, kappa: 0.099, kb_relative_information_score: 395.079, mean_absolute_error: 0.2126, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.6139, predictive_accuracy: 0.3623, prior_entropy: 2.4378, recall: 0.3623, relative_absolute_error: 0.7978, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4611, root_relative_squared_error: 1.2636, scimark_benchmark: 1368.9272, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9684, f_measure: 0.9441, kappa: 0.9301, kb_relative_information_score: 1671.3694, mean_absolute_error: 0.0279, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9444, predictive_accuracy: 0.9443, prior_entropy: 2.4378, recall: 0.9443, relative_absolute_error: 0.1049, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1354, root_relative_squared_error: 0.371, scimark_benchmark: 1341.2341, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9495, f_measure: 0.9152, kappa: 0.8957, kb_relative_information_score: 1632.1019, mean_absolute_error: 0.0277, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9153, predictive_accuracy: 0.9169, prior_entropy: 2.4378, recall: 0.9169, relative_absolute_error: 0.1039, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1664, root_relative_squared_error: 0.456, scimark_benchmark: 1386.5717, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9709, f_measure: 0.9407, kappa: 0.9247, kb_relative_information_score: 1667.9237, mean_absolute_error: 0.0275, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9435, predictive_accuracy: 0.9399, prior_entropy: 2.4378, recall: 0.9399, relative_absolute_error: 0.1032, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1381, root_relative_squared_error: 0.3784, scimark_benchmark: 1341.5768, usercpu_time_millis: 220, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9979, build_cpu_time: 121.1993, build_memory: 61507253.6, f_measure: 0.9663, kappa: 0.9576, kb_relative_information_score: 1703.8678, mean_absolute_error: 0.0268, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9669, predictive_accuracy: 0.9661, prior_entropy: 2.4378, recall: 0.9661, relative_absolute_error: 0.1008, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1009, root_relative_squared_error: 0.2765, scimark_benchmark: 941.5665,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9376, kappa: 0.9215, kb_relative_information_score: 1665.0692, mean_absolute_error: 0.03, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9384, predictive_accuracy: 0.9372, prior_entropy: 2.4378, recall: 0.9372, relative_absolute_error: 0.1124, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1343, root_relative_squared_error: 0.368, scimark_benchmark: 918.6005, usercpu_time_millis: 490, usercpu_time_millis_training: 490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, f_measure: 0.9371, kappa: 0.9208, kb_relative_information_score: 1663.8358, mean_absolute_error: 0.0301, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9378, predictive_accuracy: 0.9366, prior_entropy: 2.4378, recall: 0.9366, relative_absolute_error: 0.113, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.135, root_relative_squared_error: 0.3699, scimark_benchmark: 1307.8775, usercpu_time_millis: 320, usercpu_time_millis_training: 320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, f_measure: 0.9357, kappa: 0.9197, kb_relative_information_score: 1500.5373, mean_absolute_error: 0.0736, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9365, predictive_accuracy: 0.9361, prior_entropy: 2.4378, recall: 0.9361, relative_absolute_error: 0.2761, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1523, root_relative_squared_error: 0.4174, scimark_benchmark: 934.1747, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9972, f_measure: 0.9504, kappa: 0.9382, kb_relative_information_score: 1512.7598, mean_absolute_error: 0.0724, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9515, predictive_accuracy: 0.9508, prior_entropy: 2.4378, recall: 0.9508, relative_absolute_error: 0.2719, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1465, root_relative_squared_error: 0.4015, scimark_benchmark: 1345.8373, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9659, f_measure: 0.8934, kappa: 0.8671, kb_relative_information_score: 1588.95, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.8954, predictive_accuracy: 0.8945, prior_entropy: 2.4378, recall: 0.8945, relative_absolute_error: 0.1525, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1665, root_relative_squared_error: 0.4563, scimark_benchmark: 1333.1945, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.9203, kappa: 0.9013, kb_relative_information_score: 1638.8582, mean_absolute_error: 0.0278, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9205, predictive_accuracy: 0.9213, prior_entropy: 2.4378, recall: 0.9213, relative_absolute_error: 0.1045, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1601, root_relative_squared_error: 0.4388, scimark_benchmark: 1345.7204, usercpu_time_millis: 120, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9993, f_measure: 0.9793, kappa: 0.974, kb_relative_information_score: 1773.4513, mean_absolute_error: 0.0104, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9805, predictive_accuracy: 0.9792, prior_entropy: 2.4378, recall: 0.9792, relative_absolute_error: 0.0391, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0749, root_relative_squared_error: 0.2053, scimark_benchmark: 1343.4596, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.969, f_measure: 0.9181, kappa: 0.8983, kb_relative_information_score: 1642.6276, mean_absolute_error: 0.0324, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9207, predictive_accuracy: 0.9191, prior_entropy: 2.4378, recall: 0.9191, relative_absolute_error: 0.1216, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1473, root_relative_squared_error: 0.4038, scimark_benchmark: 1384.4422,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8342, f_measure: 0.7175, kappa: 0.6648, kb_relative_information_score: 1233.4492, mean_absolute_error: 0.088, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.7514, predictive_accuracy: 0.7361, prior_entropy: 2.4378, recall: 0.7361, relative_absolute_error: 0.3302, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.2966, root_relative_squared_error: 0.8129, scimark_benchmark: 918.0213, usercpu_time_millis: 180, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4984, f_measure: 0.1434, kb_relative_information_score: 3.6353, mean_absolute_error: 0.2666, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.0936, predictive_accuracy: 0.306, prior_entropy: 2.4378, recall: 0.306, relative_absolute_error: 1.0007, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3649, root_relative_squared_error: 1, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6526, f_measure: 0.3499, kappa: 0.3043, kb_relative_information_score: 626.6309, mean_absolute_error: 0.1729, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.3131, predictive_accuracy: 0.4814, prior_entropy: 2.4378, recall: 0.4814, relative_absolute_error: 0.6488, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4158, root_relative_squared_error: 1.1395, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.969, f_measure: 0.9181, kappa: 0.8983, kb_relative_information_score: 1642.6276, mean_absolute_error: 0.0324, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9207, predictive_accuracy: 0.9191, prior_entropy: 2.4378, recall: 0.9191, relative_absolute_error: 0.1216, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1473, root_relative_squared_error: 0.4038, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9509, f_measure: 0.9188, kappa: 0.8981, kb_relative_information_score: 1647.1946, mean_absolute_error: 0.0271, mean_prior_absolute_error: 0.2664, number_of_instances: 1830, precision: 0.9196, predictive_accuracy: 0.9186, prior_entropy: 2.4378, recall: 0.9186, relative_absolute_error: 0.1019, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1647, root_relative_squared_error: 0.4515, scimark_benchmark: 1028.5889, usercpu_time_millis: 30, usercpu_time_millis_training: 30,

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