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Function: require_once

OpenML
OpenML
Supervised Classification on waveform-5000

Supervised Classification on waveform-5000

Task 58 Supervised Classification waveform-5000 14815 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • at2 basic OpenML100 study_1 study_107 study_123 study_14 study_41 study_7 study_70 study_73 under100k under1m
Issue #Downvotes for this reason By


Metric:

14815 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8629, f_measure: 0.7456, kappa: 0.6184, kb_relative_information_score: 3240.7637, mean_absolute_error: 0.1737, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7456, predictive_accuracy: 0.7456, prior_entropy: 1.5849, recall: 0.7456, relative_absolute_error: 0.3909, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3804, root_relative_squared_error: 0.807, scimark_benchmark: 945.8332,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9572, f_measure: 0.8259, kappa: 0.7397, kb_relative_information_score: 3342.4951, mean_absolute_error: 0.1803, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8269, predictive_accuracy: 0.8264, prior_entropy: 1.5849, recall: 0.8264, relative_absolute_error: 0.4057, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2824, root_relative_squared_error: 0.5991, scimark_benchmark: 949.7065,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9307, f_measure: 0.8636, kappa: 0.7961, kb_relative_information_score: 2727.7166, mean_absolute_error: 0.2524, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8652, predictive_accuracy: 0.864, prior_entropy: 1.5849, recall: 0.864, relative_absolute_error: 0.568, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3229, root_relative_squared_error: 0.6851, scimark_benchmark: 949.8751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9003, f_measure: 0.7586, kappa: 0.6379, kb_relative_information_score: 3249.9157, mean_absolute_error: 0.1765, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7588, predictive_accuracy: 0.7586, prior_entropy: 1.5849, recall: 0.7586, relative_absolute_error: 0.3971, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3536, root_relative_squared_error: 0.7502, scimark_benchmark: 947.6458,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9534, f_measure: 0.8166, kappa: 0.7245, kb_relative_information_score: 3230.5215, mean_absolute_error: 0.1931, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8172, predictive_accuracy: 0.8164, prior_entropy: 1.5849, recall: 0.8164, relative_absolute_error: 0.4346, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2922, root_relative_squared_error: 0.62, scimark_benchmark: 948.9299,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9065, f_measure: 0.8137, kappa: 0.7204, kb_relative_information_score: 2567.8764, mean_absolute_error: 0.2637, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8137, predictive_accuracy: 0.8136, prior_entropy: 1.5849, recall: 0.8136, relative_absolute_error: 0.5934, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3398, root_relative_squared_error: 0.7209, scimark_benchmark: 948.5254,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6426, f_measure: 0.2726, kappa: 0.0802, kb_relative_information_score: 895.2072, mean_absolute_error: 0.3979, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.6964, predictive_accuracy: 0.391, prior_entropy: 1.5849, recall: 0.391, relative_absolute_error: 0.8953, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4975, root_relative_squared_error: 1.0553, scimark_benchmark: 948.3104,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9065, f_measure: 0.8137, kappa: 0.7204, kb_relative_information_score: 2567.8764, mean_absolute_error: 0.2637, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8137, predictive_accuracy: 0.8136, prior_entropy: 1.5849, recall: 0.8136, relative_absolute_error: 0.5934, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3398, root_relative_squared_error: 0.7209, scimark_benchmark: 946.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6563, f_measure: 0.5122, kappa: 0.3132, kb_relative_information_score: 1866.1554, mean_absolute_error: 0.3057, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.507, predictive_accuracy: 0.5414, prior_entropy: 1.5849, recall: 0.5414, relative_absolute_error: 0.6879, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.5529, root_relative_squared_error: 1.173, scimark_benchmark: 908.5267,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.822, f_measure: 0.6273, kappa: 0.4487, kb_relative_information_score: 1926.6636, mean_absolute_error: 0.3123, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.759, predictive_accuracy: 0.6338, prior_entropy: 1.5849, recall: 0.6338, relative_absolute_error: 0.7027, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4049, root_relative_squared_error: 0.8589, scimark_benchmark: 948.0745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1711, kb_relative_information_score: 450.9915, mean_absolute_error: 0.4427, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.1145, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9962, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1514, scimark_benchmark: 912.1038,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9708, f_measure: 0.87, kappa: 0.8053, kb_relative_information_score: 3771.5143, mean_absolute_error: 0.1333, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8703, predictive_accuracy: 0.8702, prior_entropy: 1.5849, recall: 0.8702, relative_absolute_error: 0.2999, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2512, root_relative_squared_error: 0.5329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.95, f_measure: 0.809, kappa: 0.7131, kb_relative_information_score: 3229.6241, mean_absolute_error: 0.1924, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.81, predictive_accuracy: 0.8088, prior_entropy: 1.5849, recall: 0.8088, relative_absolute_error: 0.4329, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2949, root_relative_squared_error: 0.6257, scimark_benchmark: 948.321,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9391, f_measure: 0.793, kappa: 0.6893, kb_relative_information_score: 3230.2619, mean_absolute_error: 0.188, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7968, predictive_accuracy: 0.793, prior_entropy: 1.5849, recall: 0.793, relative_absolute_error: 0.423, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3038, root_relative_squared_error: 0.6444, scimark_benchmark: 947.6467,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9287, f_measure: 0.8598, kappa: 0.7903, kb_relative_information_score: 2715.3185, mean_absolute_error: 0.2533, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8609, predictive_accuracy: 0.8602, prior_entropy: 1.5849, recall: 0.8602, relative_absolute_error: 0.57, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3243, root_relative_squared_error: 0.688, scimark_benchmark: 941.0601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8187, f_measure: 0.7485, kappa: 0.6229, kb_relative_information_score: 3213.4314, mean_absolute_error: 0.1769, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7485, predictive_accuracy: 0.7486, prior_entropy: 1.5849, recall: 0.7486, relative_absolute_error: 0.3981, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3969, root_relative_squared_error: 0.8419, scimark_benchmark: 947.5304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9107, f_measure: 0.8252, kappa: 0.7468, kb_relative_information_score: 2625.3211, mean_absolute_error: 0.2598, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8532, predictive_accuracy: 0.831, prior_entropy: 1.5849, recall: 0.831, relative_absolute_error: 0.5846, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3342, root_relative_squared_error: 0.7089, scimark_benchmark: 943.3923,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9708, f_measure: 0.87, kappa: 0.8053, kb_relative_information_score: 3771.5143, mean_absolute_error: 0.1333, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8703, predictive_accuracy: 0.8702, prior_entropy: 1.5849, recall: 0.8702, relative_absolute_error: 0.2999, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2512, root_relative_squared_error: 0.5329, scimark_benchmark: 947.8874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8186, f_measure: 0.7458, kappa: 0.6187, kb_relative_information_score: 3223.7617, mean_absolute_error: 0.1746, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7457, predictive_accuracy: 0.7458, prior_entropy: 1.5849, recall: 0.7458, relative_absolute_error: 0.3929, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4004, root_relative_squared_error: 0.8495, scimark_benchmark: 945.2598,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9166, f_measure: 0.8336, kappa: 0.7504, kb_relative_information_score: 2631.7354, mean_absolute_error: 0.2592, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8336, predictive_accuracy: 0.8336, prior_entropy: 1.5849, recall: 0.8336, relative_absolute_error: 0.5832, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3332, root_relative_squared_error: 0.7068, scimark_benchmark: 946.2504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9045, f_measure: 0.7573, kappa: 0.6368, kb_relative_information_score: 3112.7552, mean_absolute_error: 0.1936, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7576, predictive_accuracy: 0.7578, prior_entropy: 1.5849, recall: 0.7578, relative_absolute_error: 0.4357, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3505, root_relative_squared_error: 0.7436, scimark_benchmark: 941.7868,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8239, f_measure: 0.7408, kappa: 0.6112, kb_relative_information_score: 3216.061, mean_absolute_error: 0.1746, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7409, predictive_accuracy: 0.7408, prior_entropy: 1.5849, recall: 0.7408, relative_absolute_error: 0.393, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4028, root_relative_squared_error: 0.8545, scimark_benchmark: 946.6089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.8632, kappa: 0.7951, kb_relative_information_score: 2725.2443, mean_absolute_error: 0.2526, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8636, predictive_accuracy: 0.8634, prior_entropy: 1.5849, recall: 0.8634, relative_absolute_error: 0.5684, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6856, scimark_benchmark: 946.2266,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9595, f_measure: 0.8312, kappa: 0.7478, kb_relative_information_score: 3344.7056, mean_absolute_error: 0.181, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8325, predictive_accuracy: 0.8318, prior_entropy: 1.5849, recall: 0.8318, relative_absolute_error: 0.4073, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.28, root_relative_squared_error: 0.594, scimark_benchmark: 949.1451,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9315, f_measure: 0.8645, kappa: 0.7972, kb_relative_information_score: 2729.7153, mean_absolute_error: 0.2523, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8653, predictive_accuracy: 0.8648, prior_entropy: 1.5849, recall: 0.8648, relative_absolute_error: 0.5677, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3227, root_relative_squared_error: 0.6846, scimark_benchmark: 949.1457,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9598, f_measure: 0.8326, kappa: 0.7499, kb_relative_information_score: 3345.0131, mean_absolute_error: 0.1811, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8338, predictive_accuracy: 0.8332, prior_entropy: 1.5849, recall: 0.8332, relative_absolute_error: 0.4074, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2798, root_relative_squared_error: 0.5935, scimark_benchmark: 942.5006,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9314, f_measure: 0.865, kappa: 0.7978, kb_relative_information_score: 2730.9026, mean_absolute_error: 0.2522, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8654, predictive_accuracy: 0.8652, prior_entropy: 1.5849, recall: 0.8652, relative_absolute_error: 0.5675, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3226, root_relative_squared_error: 0.6844, scimark_benchmark: 938.2662,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9595, f_measure: 0.8324, kappa: 0.7496, kb_relative_information_score: 3344.6998, mean_absolute_error: 0.1809, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8337, predictive_accuracy: 0.833, prior_entropy: 1.5849, recall: 0.833, relative_absolute_error: 0.4071, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.28, root_relative_squared_error: 0.5941, scimark_benchmark: 948.327,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9231, f_measure: 0.8506, kappa: 0.7797, kb_relative_information_score: 2693.7367, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8638, predictive_accuracy: 0.853, prior_entropy: 1.5849, recall: 0.853, relative_absolute_error: 0.5736, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3268, root_relative_squared_error: 0.6932, scimark_benchmark: 944.5702,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1711, kb_relative_information_score: 450.9915, mean_absolute_error: 0.4427, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.1145, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9962, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1514, scimark_benchmark: 909.3819,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.907, f_measure: 0.7627, kappa: 0.6445, kb_relative_information_score: 3097.6301, mean_absolute_error: 0.1971, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7629, predictive_accuracy: 0.763, prior_entropy: 1.5849, recall: 0.763, relative_absolute_error: 0.4436, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3428, root_relative_squared_error: 0.7272, scimark_benchmark: 945.6836,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9557, f_measure: 0.829, kappa: 0.7438, kb_relative_information_score: 3519.41, mean_absolute_error: 0.1573, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8291, predictive_accuracy: 0.8292, prior_entropy: 1.5849, recall: 0.8292, relative_absolute_error: 0.354, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2819, root_relative_squared_error: 0.5979, scimark_benchmark: 945.9051,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9063, f_measure: 0.8132, kappa: 0.7198, kb_relative_information_score: 2566.6687, mean_absolute_error: 0.2638, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8132, predictive_accuracy: 0.8132, prior_entropy: 1.5849, recall: 0.8132, relative_absolute_error: 0.5936, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.34, root_relative_squared_error: 0.7212, scimark_benchmark: 945.3073,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9128, f_measure: 0.7554, kappa: 0.6334, kb_relative_information_score: 3135.9052, mean_absolute_error: 0.1914, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7554, predictive_accuracy: 0.7556, prior_entropy: 1.5849, recall: 0.7556, relative_absolute_error: 0.4306, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3428, root_relative_squared_error: 0.7272, scimark_benchmark: 947.7016,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9034, f_measure: 0.7636, kappa: 0.6457, kb_relative_information_score: 3208.8956, mean_absolute_error: 0.1824, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7636, predictive_accuracy: 0.7638, prior_entropy: 1.5849, recall: 0.7638, relative_absolute_error: 0.4104, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3514, root_relative_squared_error: 0.7454, scimark_benchmark: 947.0959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8226, f_measure: 0.7422, kappa: 0.6133, kb_relative_information_score: 3222.2405, mean_absolute_error: 0.1742, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7423, predictive_accuracy: 0.7422, prior_entropy: 1.5849, recall: 0.7422, relative_absolute_error: 0.3919, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4021, root_relative_squared_error: 0.853, scimark_benchmark: 947.2856,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8938, f_measure: 0.7914, kappa: 0.705, kb_relative_information_score: 2538.0444, mean_absolute_error: 0.266, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8386, predictive_accuracy: 0.803, prior_entropy: 1.5849, recall: 0.803, relative_absolute_error: 0.5986, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3434, root_relative_squared_error: 0.7284, scimark_benchmark: 946.2031,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9558, f_measure: 0.7877, kappa: 0.6999, kb_relative_information_score: 3626.7203, mean_absolute_error: 0.1356, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8336, predictive_accuracy: 0.7996, prior_entropy: 1.5849, recall: 0.7996, relative_absolute_error: 0.305, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3369, root_relative_squared_error: 0.7147, scimark_benchmark: 945.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9474, f_measure: 0.8119, kappa: 0.7183, kb_relative_information_score: 3222.0417, mean_absolute_error: 0.192, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8122, predictive_accuracy: 0.8122, prior_entropy: 1.5849, recall: 0.8122, relative_absolute_error: 0.4321, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2973, root_relative_squared_error: 0.6306, scimark_benchmark: 946.0156,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9637, f_measure: 0.8491, kappa: 0.7738, kb_relative_information_score: 3813.3816, mean_absolute_error: 0.1228, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8491, predictive_accuracy: 0.8492, prior_entropy: 1.5849, recall: 0.8492, relative_absolute_error: 0.2763, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2708, root_relative_squared_error: 0.5745, scimark_benchmark: 943.8229,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9303, f_measure: 0.8619, kappa: 0.7933, kb_relative_information_score: 2721.5942, mean_absolute_error: 0.2529, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8628, predictive_accuracy: 0.8622, prior_entropy: 1.5849, recall: 0.8622, relative_absolute_error: 0.569, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3236, root_relative_squared_error: 0.6866, scimark_benchmark: 937.9551,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.8629, kappa: 0.7949, kb_relative_information_score: 2724.7626, mean_absolute_error: 0.2527, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.864, predictive_accuracy: 0.8632, prior_entropy: 1.5849, recall: 0.8632, relative_absolute_error: 0.5685, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3233, root_relative_squared_error: 0.6858, scimark_benchmark: 910.9845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9275, f_measure: 0.8556, kappa: 0.7837, kb_relative_information_score: 2701.3355, mean_absolute_error: 0.2543, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8559, predictive_accuracy: 0.8558, prior_entropy: 1.5849, recall: 0.8558, relative_absolute_error: 0.5722, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3258, root_relative_squared_error: 0.6912, scimark_benchmark: 947.4898,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4991, f_measure: 0.1711, kb_relative_information_score: 0.311, mean_absolute_error: 0.4444, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.1145, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4714, root_relative_squared_error: 1, scimark_benchmark: 946.5097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8771, f_measure: 0.6558, kappa: 0.5238, kb_relative_information_score: 1151.6093, mean_absolute_error: 0.3771, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7232, predictive_accuracy: 0.6818, prior_entropy: 1.5849, recall: 0.6818, relative_absolute_error: 0.8486, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4106, root_relative_squared_error: 0.8711, scimark_benchmark: 945.8035,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9316, f_measure: 0.8644, kappa: 0.7969, kb_relative_information_score: 2729.0708, mean_absolute_error: 0.2524, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.865, predictive_accuracy: 0.8646, prior_entropy: 1.5849, recall: 0.8646, relative_absolute_error: 0.5678, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3228, root_relative_squared_error: 0.6848, scimark_benchmark: 945.4378,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8616, f_measure: 0.7509, kappa: 0.6265, kb_relative_information_score: 3240.5579, mean_absolute_error: 0.1748, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7509, predictive_accuracy: 0.751, prior_entropy: 1.5849, recall: 0.751, relative_absolute_error: 0.3934, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.378, root_relative_squared_error: 0.802, scimark_benchmark: 947.3547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8203, f_measure: 0.7455, kappa: 0.6184, kb_relative_information_score: 3217.7972, mean_absolute_error: 0.1754, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7455, predictive_accuracy: 0.7456, prior_entropy: 1.5849, recall: 0.7456, relative_absolute_error: 0.3947, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4002, root_relative_squared_error: 0.8489, scimark_benchmark: 949.3126,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.1711, kb_relative_information_score: 450.9915, mean_absolute_error: 0.4427, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.1145, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9962, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.5427, root_relative_squared_error: 1.1514, scimark_benchmark: 948.6488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9235, f_measure: 0.772, kappa: 0.6583, kb_relative_information_score: 3247.8389, mean_absolute_error: 0.1841, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7818, predictive_accuracy: 0.7724, prior_entropy: 1.5849, recall: 0.7724, relative_absolute_error: 0.4142, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3157, root_relative_squared_error: 0.6698, scimark_benchmark: 946.1839,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9292, f_measure: 0.861, kappa: 0.7922, kb_relative_information_score: 2719.4937, mean_absolute_error: 0.253, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8624, predictive_accuracy: 0.8614, prior_entropy: 1.5849, recall: 0.8614, relative_absolute_error: 0.5693, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3238, root_relative_squared_error: 0.687, scimark_benchmark: 944.3018,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9648, f_measure: 0.8488, kappa: 0.7735, kb_relative_information_score: 3788.4064, mean_absolute_error: 0.1268, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8489, predictive_accuracy: 0.849, prior_entropy: 1.5849, recall: 0.849, relative_absolute_error: 0.2852, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2668, root_relative_squared_error: 0.5661, scimark_benchmark: 949.213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9419, f_measure: 0.8071, kappa: 0.7111, kb_relative_information_score: 3230.3551, mean_absolute_error: 0.19, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8073, predictive_accuracy: 0.8074, prior_entropy: 1.5849, recall: 0.8074, relative_absolute_error: 0.4275, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3017, root_relative_squared_error: 0.6401, scimark_benchmark: 945.437,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8397, f_measure: 0.7603, kappa: 0.6413, kb_relative_information_score: 3167.9512, mean_absolute_error: 0.1865, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7608, predictive_accuracy: 0.7608, prior_entropy: 1.5849, recall: 0.7608, relative_absolute_error: 0.4196, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3778, root_relative_squared_error: 0.8014, scimark_benchmark: 945.6745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.945, f_measure: 0.798, kappa: 0.6966, kb_relative_information_score: 3229.3366, mean_absolute_error: 0.1908, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8, predictive_accuracy: 0.7978, prior_entropy: 1.5849, recall: 0.7978, relative_absolute_error: 0.4293, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.2991, root_relative_squared_error: 0.6345, scimark_benchmark: 946.7698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9339, f_measure: 0.7981, kappa: 0.6976, kb_relative_information_score: 3252.3918, mean_absolute_error: 0.1853, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7982, predictive_accuracy: 0.7984, prior_entropy: 1.5849, recall: 0.7984, relative_absolute_error: 0.4169, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3074, root_relative_squared_error: 0.6522, scimark_benchmark: 881.0489,

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