OpenML
Supervised Classification on dermatology

Supervised Classification on dermatology

Task 35 Supervised Classification dermatology 673 runs submitted
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  • basic study_1 study_107 study_123 study_41 study_50 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9932, f_measure: 0.9726, kappa: 0.9658, kb_relative_information_score: 352.5952, mean_absolute_error: 0.0092, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9727, predictive_accuracy: 0.9727, prior_entropy: 2.4378, recall: 0.9727, relative_absolute_error: 0.0344, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0954, root_relative_squared_error: 0.2615, scimark_benchmark: 944.5663,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9972, f_measure: 0.9754, kappa: 0.9692, kb_relative_information_score: 342.9966, mean_absolute_error: 0.0248, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9758, predictive_accuracy: 0.9754, prior_entropy: 2.4378, recall: 0.9754, relative_absolute_error: 0.0931, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0922, root_relative_squared_error: 0.2528, scimark_benchmark: 947.4836,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, f_measure: 0.9728, kappa: 0.9658, kb_relative_information_score: 349.5639, mean_absolute_error: 0.0141, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9731, predictive_accuracy: 0.9727, prior_entropy: 2.4378, recall: 0.9727, relative_absolute_error: 0.0529, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0931, root_relative_squared_error: 0.2552, scimark_benchmark: 941.5961,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6755, f_measure: 0.3497, kappa: 0.3397, kb_relative_information_score: 132.1776, mean_absolute_error: 0.1658, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.2755, predictive_accuracy: 0.5027, prior_entropy: 2.4378, recall: 0.5027, relative_absolute_error: 0.6221, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4071, root_relative_squared_error: 1.1158, scimark_benchmark: 936.9369,
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, f_measure: 0.9616, kappa: 0.9521, kb_relative_information_score: 323.8253, mean_absolute_error: 0.0482, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9615, predictive_accuracy: 0.9617, prior_entropy: 2.4378, recall: 0.9617, relative_absolute_error: 0.1807, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.124, root_relative_squared_error: 0.3399, scimark_benchmark: 939.7057,
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9929, f_measure: 0.9587, kappa: 0.9486, kb_relative_information_score: 342.4624, mean_absolute_error: 0.017, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9594, predictive_accuracy: 0.959, prior_entropy: 2.4378, recall: 0.959, relative_absolute_error: 0.0637, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1155, root_relative_squared_error: 0.3166, scimark_benchmark: 929.6714,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9987, f_measure: 0.9753, kappa: 0.9692, kb_relative_information_score: 323.4392, mean_absolute_error: 0.0508, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9753, predictive_accuracy: 0.9754, prior_entropy: 2.4378, recall: 0.9754, relative_absolute_error: 0.1908, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1153, root_relative_squared_error: 0.316, scimark_benchmark: 942.8339,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9918, f_measure: 0.9726, kappa: 0.9658, kb_relative_information_score: 353.2799, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.973, predictive_accuracy: 0.9727, prior_entropy: 2.4378, recall: 0.9727, relative_absolute_error: 0.0343, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0943, root_relative_squared_error: 0.2585, scimark_benchmark: 931.0531,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, f_measure: 0.9616, kappa: 0.9521, kb_relative_information_score: 323.8253, mean_absolute_error: 0.0482, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9615, predictive_accuracy: 0.9617, prior_entropy: 2.4378, recall: 0.9617, relative_absolute_error: 0.1807, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.124, root_relative_squared_error: 0.3399, scimark_benchmark: 936.221,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7686, f_measure: 0.3497, kappa: 0.3397, kb_relative_information_score: 134.3949, mean_absolute_error: 0.2033, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.2755, predictive_accuracy: 0.5027, prior_entropy: 2.4378, recall: 0.5027, relative_absolute_error: 0.763, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3191, root_relative_squared_error: 0.8744, scimark_benchmark: 933.6028,
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, f_measure: 0.9588, kappa: 0.9486, kb_relative_information_score: 346.9474, mean_absolute_error: 0.0147, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9596, predictive_accuracy: 0.959, prior_entropy: 2.4378, recall: 0.959, relative_absolute_error: 0.055, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.112, root_relative_squared_error: 0.3069, scimark_benchmark: 948.1141,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9989, f_measure: 0.9645, kappa: 0.9555, kb_relative_information_score: 350.9733, mean_absolute_error: 0.0148, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9648, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.0555, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0812, root_relative_squared_error: 0.2224, scimark_benchmark: 946.0677,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.9647, kappa: 0.9555, kb_relative_information_score: 347.0922, mean_absolute_error: 0.0175, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9649, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.0658, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0938, root_relative_squared_error: 0.2571, scimark_benchmark: 943.8826,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7909, f_measure: 0.3566, kappa: 0.3377, kb_relative_information_score: 130.3329, mean_absolute_error: 0.1973, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.2924, predictive_accuracy: 0.4973, prior_entropy: 2.4378, recall: 0.4973, relative_absolute_error: 0.7404, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3159, root_relative_squared_error: 0.8657, scimark_benchmark: 924.0111,
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9934, f_measure: 0.9619, kappa: 0.952, kb_relative_information_score: 343.1041, mean_absolute_error: 0.0227, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9624, predictive_accuracy: 0.9617, prior_entropy: 2.4378, recall: 0.9617, relative_absolute_error: 0.0853, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1033, root_relative_squared_error: 0.2832, scimark_benchmark: 918.1872,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9899, f_measure: 0.9645, kappa: 0.9555, kb_relative_information_score: 349.0211, mean_absolute_error: 0.0118, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9645, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.0445, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1086, root_relative_squared_error: 0.2977, scimark_benchmark: 943.7143,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.995, f_measure: 0.9562, kappa: 0.9451, kb_relative_information_score: 342.7477, mean_absolute_error: 0.0173, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9581, predictive_accuracy: 0.9563, prior_entropy: 2.4378, recall: 0.9563, relative_absolute_error: 0.0649, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1129, root_relative_squared_error: 0.3094, scimark_benchmark: 946.6699,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9975, f_measure: 0.9376, kappa: 0.9214, kb_relative_information_score: 321.1097, mean_absolute_error: 0.0499, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9404, predictive_accuracy: 0.9372, prior_entropy: 2.4378, recall: 0.9372, relative_absolute_error: 0.1871, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1261, root_relative_squared_error: 0.3456, scimark_benchmark: 944.288,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9727, f_measure: 0.9101, kappa: 0.8871, kb_relative_information_score: 323.4141, mean_absolute_error: 0.0391, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9126, predictive_accuracy: 0.9098, prior_entropy: 2.4378, recall: 0.9098, relative_absolute_error: 0.1467, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1551, root_relative_squared_error: 0.4251, scimark_benchmark: 905.3617,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4867, f_measure: 0.1434, kb_relative_information_score: 0.2706, mean_absolute_error: 0.2665, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.0936, predictive_accuracy: 0.306, prior_entropy: 2.4378, recall: 0.306, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3649, root_relative_squared_error: 1.0001, scimark_benchmark: 949.5029,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, f_measure: 0.967, kappa: 0.9589, kb_relative_information_score: 328.0517, mean_absolute_error: 0.0424, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9677, predictive_accuracy: 0.9672, prior_entropy: 2.4378, recall: 0.9672, relative_absolute_error: 0.1593, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1185, root_relative_squared_error: 0.3247, scimark_benchmark: 927.1409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9873, f_measure: 0.9671, kappa: 0.9589, kb_relative_information_score: 125.5521, mean_absolute_error: 0.223, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9671, predictive_accuracy: 0.9672, prior_entropy: 2.4378, recall: 0.9672, relative_absolute_error: 0.837, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3114, root_relative_squared_error: 0.8535, scimark_benchmark: 949.2319,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.986, f_measure: 0.9643, kappa: 0.9555, kb_relative_information_score: 125.42, mean_absolute_error: 0.2231, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9642, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3116, root_relative_squared_error: 0.8539, scimark_benchmark: 950.4229,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5098, f_measure: 0.1434, kb_relative_information_score: 23.1066, mean_absolute_error: 0.261, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.0936, predictive_accuracy: 0.306, prior_entropy: 2.4378, recall: 0.306, relative_absolute_error: 0.9796, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3676, root_relative_squared_error: 1.0073, scimark_benchmark: 942.2225,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9956, f_measure: 0.9669, kappa: 0.959, kb_relative_information_score: 349.8828, mean_absolute_error: 0.0123, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9669, predictive_accuracy: 0.9672, prior_entropy: 2.4378, recall: 0.9672, relative_absolute_error: 0.046, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1042, root_relative_squared_error: 0.2856, scimark_benchmark: 920.0503,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9285, kappa: 0.9106, kb_relative_information_score: 322.4521, mean_absolute_error: 0.0432, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9309, predictive_accuracy: 0.929, prior_entropy: 2.4378, recall: 0.929, relative_absolute_error: 0.1622, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1313, root_relative_squared_error: 0.36, scimark_benchmark: 949.2288,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, f_measure: 0.9697, kappa: 0.9624, kb_relative_information_score: 352.1672, mean_absolute_error: 0.0109, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9696, predictive_accuracy: 0.9699, prior_entropy: 2.4378, recall: 0.9699, relative_absolute_error: 0.041, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.0921, root_relative_squared_error: 0.2524, scimark_benchmark: 922.3546,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9942, f_measure: 0.9338, kappa: 0.9175, kb_relative_information_score: 322.7103, mean_absolute_error: 0.0426, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.935, predictive_accuracy: 0.9344, prior_entropy: 2.4378, recall: 0.9344, relative_absolute_error: 0.16, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1314, root_relative_squared_error: 0.36, scimark_benchmark: 925.8322,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6541, f_measure: 0.2313, kappa: 0.0817, kb_relative_information_score: 45.5882, mean_absolute_error: 0.2525, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.5411, predictive_accuracy: 0.3552, prior_entropy: 2.4378, recall: 0.3552, relative_absolute_error: 0.9475, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3557, root_relative_squared_error: 0.9749, scimark_benchmark: 946.8385,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6755, f_measure: 0.3497, kappa: 0.3397, kb_relative_information_score: 132.1776, mean_absolute_error: 0.1658, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.2755, predictive_accuracy: 0.5027, prior_entropy: 2.4378, recall: 0.5027, relative_absolute_error: 0.6221, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.4071, root_relative_squared_error: 1.1158, scimark_benchmark: 925.9658,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7686, f_measure: 0.3497, kappa: 0.3397, kb_relative_information_score: 134.3949, mean_absolute_error: 0.2033, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.2755, predictive_accuracy: 0.5027, prior_entropy: 2.4378, recall: 0.5027, relative_absolute_error: 0.763, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3191, root_relative_squared_error: 0.8744, scimark_benchmark: 924.7435,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9517, f_measure: 0.8636, kappa: 0.8307, kb_relative_information_score: 196.9628, mean_absolute_error: 0.1602, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.8684, predictive_accuracy: 0.8661, prior_entropy: 2.4378, recall: 0.8661, relative_absolute_error: 0.6012, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.2484, root_relative_squared_error: 0.6809, scimark_benchmark: 948.3155,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7328, f_measure: 0.3579, kappa: 0.2129, kb_relative_information_score: 61.3431, mean_absolute_error: 0.2466, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.7311, predictive_accuracy: 0.4372, prior_entropy: 2.4378, recall: 0.4372, relative_absolute_error: 0.9254, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3473, root_relative_squared_error: 0.9519, scimark_benchmark: 949.1174,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9668, f_measure: 0.9148, kappa: 0.8935, kb_relative_information_score: 326.2062, mean_absolute_error: 0.0353, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9161, predictive_accuracy: 0.9153, prior_entropy: 2.4378, recall: 0.9153, relative_absolute_error: 0.1324, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1578, root_relative_squared_error: 0.4325, scimark_benchmark: 916.8472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5037, f_measure: 0.1434, kb_relative_information_score: 23.1671, mean_absolute_error: 0.2612, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.0936, predictive_accuracy: 0.306, prior_entropy: 2.4378, recall: 0.306, relative_absolute_error: 0.9803, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3678, root_relative_squared_error: 1.008, scimark_benchmark: 942.8507,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9938, f_measure: 0.9285, kappa: 0.9106, kb_relative_information_score: 322.3141, mean_absolute_error: 0.0438, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9309, predictive_accuracy: 0.929, prior_entropy: 2.4378, recall: 0.929, relative_absolute_error: 0.1642, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1314, root_relative_squared_error: 0.3602, scimark_benchmark: 944.7336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.986, f_measure: 0.9643, kappa: 0.9555, kb_relative_information_score: 125.42, mean_absolute_error: 0.2231, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9642, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3116, root_relative_squared_error: 0.8539, scimark_benchmark: 909.2928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9965, f_measure: 0.9532, kappa: 0.9417, kb_relative_information_score: 317.8009, mean_absolute_error: 0.0534, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9538, predictive_accuracy: 0.9536, prior_entropy: 2.4378, recall: 0.9536, relative_absolute_error: 0.2004, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1305, root_relative_squared_error: 0.3578, scimark_benchmark: 947.0409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9659, f_measure: 0.8993, kappa: 0.8735, kb_relative_information_score: 311.121, mean_absolute_error: 0.048, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9021, predictive_accuracy: 0.8989, prior_entropy: 2.4378, recall: 0.8989, relative_absolute_error: 0.1802, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1717, root_relative_squared_error: 0.4707, scimark_benchmark: 945.143,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9758, f_measure: 0.9375, kappa: 0.9214, kb_relative_information_score: 337.5182, mean_absolute_error: 0.0252, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9388, predictive_accuracy: 0.9372, prior_entropy: 2.4378, recall: 0.9372, relative_absolute_error: 0.0944, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1355, root_relative_squared_error: 0.3713, scimark_benchmark: 913.9914,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5056, f_measure: 0.1545, kappa: 0.0092, kb_relative_information_score: 23.7717, mean_absolute_error: 0.261, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.228, predictive_accuracy: 0.3115, prior_entropy: 2.4378, recall: 0.3115, relative_absolute_error: 0.9794, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3675, root_relative_squared_error: 1.0071, scimark_benchmark: 946.3476,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9987, f_measure: 0.967, kappa: 0.9589, kb_relative_information_score: 321.6983, mean_absolute_error: 0.0523, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9671, predictive_accuracy: 0.9672, prior_entropy: 2.4378, recall: 0.9672, relative_absolute_error: 0.1964, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.119, root_relative_squared_error: 0.3261, scimark_benchmark: 946.6672,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9976, f_measure: 0.9649, kappa: 0.9555, kb_relative_information_score: 341.2464, mean_absolute_error: 0.0264, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9657, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.0991, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1033, root_relative_squared_error: 0.283, scimark_benchmark: 923.2983,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.973, f_measure: 0.9295, kappa: 0.9112, kb_relative_information_score: 338.2338, mean_absolute_error: 0.0239, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9306, predictive_accuracy: 0.929, prior_entropy: 2.4378, recall: 0.929, relative_absolute_error: 0.0899, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1384, root_relative_squared_error: 0.3794, scimark_benchmark: 944.7463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.531, f_measure: 0.1545, kappa: 0.0092, kb_relative_information_score: 26.1226, mean_absolute_error: 0.2597, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.228, predictive_accuracy: 0.3115, prior_entropy: 2.4378, recall: 0.3115, relative_absolute_error: 0.9748, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3658, root_relative_squared_error: 1.0026, scimark_benchmark: 950.0063,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.985, f_measure: 0.9589, kappa: 0.9487, kb_relative_information_score: 125.288, mean_absolute_error: 0.2231, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9587, predictive_accuracy: 0.959, prior_entropy: 2.4378, recall: 0.959, relative_absolute_error: 0.8374, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3117, root_relative_squared_error: 0.8542, scimark_benchmark: 932.0062,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9827, f_measure: 0.8601, kappa: 0.8477, kb_relative_information_score: 267.6501, mean_absolute_error: 0.088, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.8506, predictive_accuracy: 0.8798, prior_entropy: 2.4378, recall: 0.8798, relative_absolute_error: 0.3302, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.2034, root_relative_squared_error: 0.5575, scimark_benchmark: 920.3633,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9311, kappa: 0.914, kb_relative_information_score: 322.1776, mean_absolute_error: 0.0431, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9331, predictive_accuracy: 0.9317, prior_entropy: 2.4378, recall: 0.9317, relative_absolute_error: 0.1619, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1321, root_relative_squared_error: 0.3621, scimark_benchmark: 947.7313,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9989, f_measure: 0.9646, kappa: 0.9555, kb_relative_information_score: 332.0501, mean_absolute_error: 0.0398, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9651, predictive_accuracy: 0.9645, prior_entropy: 2.4378, recall: 0.9645, relative_absolute_error: 0.1495, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.1141, root_relative_squared_error: 0.3127, scimark_benchmark: 948.22,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9873, f_measure: 0.9671, kappa: 0.9589, kb_relative_information_score: 125.5521, mean_absolute_error: 0.223, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.9671, predictive_accuracy: 0.9672, prior_entropy: 2.4378, recall: 0.9672, relative_absolute_error: 0.837, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3114, root_relative_squared_error: 0.8535, scimark_benchmark: 946.9433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1434, kb_relative_information_score: 22.6075, mean_absolute_error: 0.2614, mean_prior_absolute_error: 0.2664, number_of_instances: 366, precision: 0.0936, predictive_accuracy: 0.306, prior_entropy: 2.4378, recall: 0.306, relative_absolute_error: 0.9812, root_mean_prior_squared_error: 0.3649, root_mean_squared_error: 0.3681, root_relative_squared_error: 1.0089, scimark_benchmark: 944.7152,

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