OpenML
Supervised Classification on kr-vs-kp

Supervised Classification on kr-vs-kp

Task 1767 Supervised Classification kr-vs-kp 356 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.994, f_measure: 0.9707, kappa: 0.9413, kb_relative_information_score: 14687.6695, mean_absolute_error: 0.0428, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9707, predictive_accuracy: 0.9707, prior_entropy: 0.9986, recall: 0.9707, relative_absolute_error: 0.0858, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1561, root_relative_squared_error: 0.3125, scimark_benchmark: 1084.7303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9955, build_cpu_time: 0.0345, build_memory: 33843716.8, f_measure: 0.9904, kappa: 0.9807, kb_relative_information_score: 15559.2526, mean_absolute_error: 0.0143, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9904, predictive_accuracy: 0.9904, prior_entropy: 0.9986, recall: 0.9904, relative_absolute_error: 0.0287, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0965, root_relative_squared_error: 0.1932, scimark_benchmark: 944.601,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9955, build_cpu_time: 0.0174, build_memory: 47949952.8, f_measure: 0.9904, kappa: 0.9807, kb_relative_information_score: 15559.2526, mean_absolute_error: 0.0143, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9904, predictive_accuracy: 0.9904, prior_entropy: 0.9986, recall: 0.9904, relative_absolute_error: 0.0287, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0965, root_relative_squared_error: 0.1932, scimark_benchmark: 931.055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9984, build_cpu_time: 0.2276, build_memory: 2057823550.4, f_measure: 0.9901, kappa: 0.9801, kb_relative_information_score: 15450.3467, mean_absolute_error: 0.0184, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9901, predictive_accuracy: 0.9901, prior_entropy: 0.9986, recall: 0.9901, relative_absolute_error: 0.0368, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0899, root_relative_squared_error: 0.1799, scimark_benchmark: 940.5901,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, build_cpu_time: 0.4315, build_memory: 105908113.6, f_measure: 0.9909, kappa: 0.9817, kb_relative_information_score: 15461.7486, mean_absolute_error: 0.0181, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9909, predictive_accuracy: 0.9909, prior_entropy: 0.9986, recall: 0.9909, relative_absolute_error: 0.0362, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0882, root_relative_squared_error: 0.1767, scimark_benchmark: 904.647,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9986, build_cpu_time: 0.7554, build_memory: 1321590896.8, f_measure: 0.9907, kappa: 0.9814, kb_relative_information_score: 15461.6569, mean_absolute_error: 0.0181, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9907, predictive_accuracy: 0.9907, prior_entropy: 0.9986, recall: 0.9907, relative_absolute_error: 0.0362, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0882, root_relative_squared_error: 0.1766, scimark_benchmark: 923.1007,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, build_cpu_time: 1.4289, build_memory: 2186851474.4, f_measure: 0.9905, kappa: 0.9809, kb_relative_information_score: 15461.2626, mean_absolute_error: 0.0181, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9905, predictive_accuracy: 0.9905, prior_entropy: 0.9986, recall: 0.9905, relative_absolute_error: 0.0363, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0883, root_relative_squared_error: 0.1768, scimark_benchmark: 946.6769,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, build_cpu_time: 15.6969, build_memory: 191847070.4, f_measure: 0.9884, kappa: 0.9768, kb_relative_information_score: 15231.563, mean_absolute_error: 0.0267, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9884, predictive_accuracy: 0.9884, prior_entropy: 0.9986, recall: 0.9884, relative_absolute_error: 0.0535, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.098, root_relative_squared_error: 0.1962, scimark_benchmark: 946.5913,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.996, build_cpu_time: 0.4201, build_memory: 434302810.4, f_measure: 0.9637, kappa: 0.9272, kb_relative_information_score: 14894.1321, mean_absolute_error: 0.0338, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9638, predictive_accuracy: 0.9636, prior_entropy: 0.9986, recall: 0.9636, relative_absolute_error: 0.0677, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1682, root_relative_squared_error: 0.3367, scimark_benchmark: 945.0342,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9973, build_cpu_time: 1.2063, build_memory: 84551824.8, f_measure: 0.9797, kappa: 0.9594, kb_relative_information_score: 15313.6549, mean_absolute_error: 0.0209, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9797, predictive_accuracy: 0.9797, prior_entropy: 0.9986, recall: 0.9797, relative_absolute_error: 0.0418, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1337, root_relative_squared_error: 0.2677, scimark_benchmark: 938.2803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9973, build_cpu_time: 1.766, build_memory: 1125770644.8, f_measure: 0.9797, kappa: 0.9594, kb_relative_information_score: 15313.6549, mean_absolute_error: 0.0209, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9797, predictive_accuracy: 0.9797, prior_entropy: 0.9986, recall: 0.9797, relative_absolute_error: 0.0418, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1337, root_relative_squared_error: 0.2677, scimark_benchmark: 944.2618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9976, build_cpu_time: 2.9137, build_memory: 865506390.4, f_measure: 0.9874, kappa: 0.9747, kb_relative_information_score: 15567.5628, mean_absolute_error: 0.013, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9874, predictive_accuracy: 0.9874, prior_entropy: 0.9986, recall: 0.9874, relative_absolute_error: 0.026, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1054, root_relative_squared_error: 0.211, scimark_benchmark: 945.0342,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9976, build_cpu_time: 3.0154, build_memory: 732168982.4, f_measure: 0.9874, kappa: 0.9747, kb_relative_information_score: 15567.5628, mean_absolute_error: 0.013, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9874, predictive_accuracy: 0.9874, prior_entropy: 0.9986, recall: 0.9874, relative_absolute_error: 0.026, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1054, root_relative_squared_error: 0.211, scimark_benchmark: 944.7154,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9971, build_cpu_time: 3.7808, build_memory: 1172283804.8, f_measure: 0.9916, kappa: 0.9831, kb_relative_information_score: 15711.0132, mean_absolute_error: 0.0084, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9916, predictive_accuracy: 0.9916, prior_entropy: 0.9986, recall: 0.9916, relative_absolute_error: 0.0168, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0882, root_relative_squared_error: 0.1767, scimark_benchmark: 944.5683,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, build_cpu_time: 7.9998, build_memory: 874956805.6, f_measure: 0.9939, kappa: 0.9878, kb_relative_information_score: 15782.7787, mean_absolute_error: 0.0062, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9939, predictive_accuracy: 0.9939, prior_entropy: 0.9986, recall: 0.9939, relative_absolute_error: 0.0123, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0768, root_relative_squared_error: 0.1538, scimark_benchmark: 931.9798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, build_cpu_time: 643.2598, build_memory: 1887126352, f_measure: 0.9929, kappa: 0.9858, kb_relative_information_score: 15583.7342, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.993, predictive_accuracy: 0.9929, prior_entropy: 0.9986, recall: 0.9929, relative_absolute_error: 0.0276, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0795, root_relative_squared_error: 0.1592, scimark_benchmark: 944.0892,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, build_cpu_time: 85.4605, build_memory: 202114160, f_measure: 0.9926, kappa: 0.9852, kb_relative_information_score: 15581.9159, mean_absolute_error: 0.0137, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9926, predictive_accuracy: 0.9926, prior_entropy: 0.9986, recall: 0.9926, relative_absolute_error: 0.0275, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0807, root_relative_squared_error: 0.1615, scimark_benchmark: 941.326,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, build_cpu_time: 2.3185, build_memory: 659593652, f_measure: 0.9867, kappa: 0.9734, kb_relative_information_score: 14288.8794, mean_absolute_error: 0.063, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9867, predictive_accuracy: 0.9867, prior_entropy: 0.9986, recall: 0.9867, relative_absolute_error: 0.1262, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1301, root_relative_squared_error: 0.2604, scimark_benchmark: 939.4327,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9986, build_cpu_time: 0.7129, build_memory: 412612984, f_measure: 0.9875, kappa: 0.9749, kb_relative_information_score: 15400.1741, mean_absolute_error: 0.0195, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9875, predictive_accuracy: 0.9875, prior_entropy: 0.9986, recall: 0.9875, relative_absolute_error: 0.039, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1031, root_relative_squared_error: 0.2064, scimark_benchmark: 892.0716,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, build_cpu_time: 28.3938, build_memory: 1418735614.4, f_measure: 0.9929, kappa: 0.9858, kb_relative_information_score: 15752.3241, mean_absolute_error: 0.0071, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9929, predictive_accuracy: 0.9929, prior_entropy: 0.9986, recall: 0.9929, relative_absolute_error: 0.0142, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0837, root_relative_squared_error: 0.1675, scimark_benchmark: 947.7459,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9931, build_cpu_time: 55.5171, build_memory: 2278938975.2, f_measure: 0.9928, kappa: 0.9856, kb_relative_information_score: 15750.3465, mean_absolute_error: 0.0072, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9928, predictive_accuracy: 0.9928, prior_entropy: 0.9986, recall: 0.9928, relative_absolute_error: 0.0143, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0844, root_relative_squared_error: 0.1689, scimark_benchmark: 944.1141,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, build_cpu_time: 0.4696, build_memory: 622561360.8, f_measure: 0.9531, kappa: 0.906, kb_relative_information_score: 13895.3406, mean_absolute_error: 0.0706, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9533, predictive_accuracy: 0.9531, prior_entropy: 0.9986, recall: 0.9531, relative_absolute_error: 0.1415, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1808, root_relative_squared_error: 0.3619, scimark_benchmark: 873.8637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9912, build_cpu_time: 0.2886, build_memory: 590197222.4, f_measure: 0.9498, kappa: 0.8994, kb_relative_information_score: 13491.6038, mean_absolute_error: 0.0855, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9501, predictive_accuracy: 0.9499, prior_entropy: 0.9986, recall: 0.9499, relative_absolute_error: 0.1713, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.192, root_relative_squared_error: 0.3844, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.969, build_cpu_time: 0.5178, build_memory: 104511364.8, f_measure: 0.9271, kappa: 0.8539, kb_relative_information_score: 12712.2911, mean_absolute_error: 0.1075, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9293, predictive_accuracy: 0.9273, prior_entropy: 0.9986, recall: 0.9273, relative_absolute_error: 0.2155, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.2498, root_relative_squared_error: 0.5002, scimark_benchmark: 873.8637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.969, build_cpu_time: 0.4916, build_memory: 967055699.2, f_measure: 0.9271, kappa: 0.8539, kb_relative_information_score: 12712.2911, mean_absolute_error: 0.1075, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9293, predictive_accuracy: 0.9273, prior_entropy: 0.9986, recall: 0.9273, relative_absolute_error: 0.2155, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.2498, root_relative_squared_error: 0.5002, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9937, build_cpu_time: 3.6796, build_memory: 109292296.8, f_measure: 0.9934, kappa: 0.9867, kb_relative_information_score: 15768.3347, mean_absolute_error: 0.0066, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9934, predictive_accuracy: 0.9934, prior_entropy: 0.9986, recall: 0.9934, relative_absolute_error: 0.0132, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0811, root_relative_squared_error: 0.1624, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, build_cpu_time: 1.8198, build_memory: 1432504430.4, f_measure: 0.9937, kappa: 0.9873, kb_relative_information_score: 15776.9358, mean_absolute_error: 0.0063, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9937, predictive_accuracy: 0.9937, prior_entropy: 0.9986, recall: 0.9937, relative_absolute_error: 0.0127, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0795, root_relative_squared_error: 0.1592, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9946, build_cpu_time: 1.1215, build_memory: 150567796, f_measure: 0.9936, kappa: 0.9872, kb_relative_information_score: 15774.7266, mean_absolute_error: 0.0064, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9936, predictive_accuracy: 0.9936, prior_entropy: 0.9986, recall: 0.9936, relative_absolute_error: 0.0128, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0793, root_relative_squared_error: 0.1588, scimark_benchmark: 934.2858,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9949, build_cpu_time: 0.4652, build_memory: 108716640, f_measure: 0.9932, kappa: 0.9865, kb_relative_information_score: 15765.0089, mean_absolute_error: 0.0067, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9933, predictive_accuracy: 0.9932, prior_entropy: 0.9986, recall: 0.9932, relative_absolute_error: 0.0134, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0807, root_relative_squared_error: 0.1615, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9962, build_cpu_time: 0.3594, build_memory: 1031462548, f_measure: 0.9932, kappa: 0.9863, kb_relative_information_score: 15761.0226, mean_absolute_error: 0.0068, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9932, predictive_accuracy: 0.9932, prior_entropy: 0.9986, recall: 0.9932, relative_absolute_error: 0.0137, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0808, root_relative_squared_error: 0.1618, scimark_benchmark: 943.4039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9978, build_cpu_time: 0.9433, build_memory: 840488823.2, f_measure: 0.992, kappa: 0.9839, kb_relative_information_score: 15724.2994, mean_absolute_error: 0.008, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.992, predictive_accuracy: 0.992, prior_entropy: 0.9986, recall: 0.992, relative_absolute_error: 0.016, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0847, root_relative_squared_error: 0.1695, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9966, build_cpu_time: 1.4943, build_memory: 1108101739.2, f_measure: 0.9926, kappa: 0.9852, kb_relative_information_score: 15738.2714, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9926, predictive_accuracy: 0.9926, prior_entropy: 0.9986, recall: 0.9926, relative_absolute_error: 0.0151, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0842, root_relative_squared_error: 0.1686, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.996, build_cpu_time: 2.2224, build_memory: 2915139080, f_measure: 0.9928, kappa: 0.9856, kb_relative_information_score: 15750.7507, mean_absolute_error: 0.0072, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9928, predictive_accuracy: 0.9928, prior_entropy: 0.9986, recall: 0.9928, relative_absolute_error: 0.0143, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0829, root_relative_squared_error: 0.1659, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, build_cpu_time: 3.1786, build_memory: 190207368, f_measure: 0.9931, kappa: 0.9862, kb_relative_information_score: 15751.983, mean_absolute_error: 0.0071, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9931, predictive_accuracy: 0.9931, prior_entropy: 0.9986, recall: 0.9931, relative_absolute_error: 0.0143, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0825, root_relative_squared_error: 0.1653, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, build_cpu_time: 51.9953, build_memory: 940522086.4, f_measure: 0.994, kappa: 0.988, kb_relative_information_score: 15785.1653, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.994, predictive_accuracy: 0.994, prior_entropy: 0.9986, recall: 0.994, relative_absolute_error: 0.0122, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0769, root_relative_squared_error: 0.154, scimark_benchmark: 890.3066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9978, build_cpu_time: 23.7448, build_memory: 875555034.4, f_measure: 0.9937, kappa: 0.9875, kb_relative_information_score: 15775.5095, mean_absolute_error: 0.0064, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9937, predictive_accuracy: 0.9937, prior_entropy: 0.9986, recall: 0.9937, relative_absolute_error: 0.0128, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.077, root_relative_squared_error: 0.1542, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9986, build_cpu_time: 14.8147, build_memory: 314350919.2, f_measure: 0.9934, kappa: 0.9868, kb_relative_information_score: 15760.3474, mean_absolute_error: 0.0069, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9934, predictive_accuracy: 0.9934, prior_entropy: 0.9986, recall: 0.9934, relative_absolute_error: 0.0139, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0759, root_relative_squared_error: 0.152, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, build_cpu_time: 6.5572, build_memory: 342792331.2, f_measure: 0.9924, kappa: 0.9847, kb_relative_information_score: 15697.3831, mean_absolute_error: 0.0092, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9924, predictive_accuracy: 0.9924, prior_entropy: 0.9986, recall: 0.9924, relative_absolute_error: 0.0184, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0796, root_relative_squared_error: 0.1594, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9989, build_cpu_time: 3.939, build_memory: 144500609.6, f_measure: 0.9879, kappa: 0.9758, kb_relative_information_score: 15466.5029, mean_absolute_error: 0.0171, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9879, predictive_accuracy: 0.9879, prior_entropy: 0.9986, recall: 0.9879, relative_absolute_error: 0.0343, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0984, root_relative_squared_error: 0.1969, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9953, build_cpu_time: 65.1353, build_memory: 1350799871.2, f_measure: 0.9923, kappa: 0.9846, kb_relative_information_score: 15731.8247, mean_absolute_error: 0.0078, mean_prior_absolute_error: 0.499, number_of_instances: 15980, precision: 0.9923, predictive_accuracy: 0.9923, prior_entropy: 0.9986, recall: 0.9923, relative_absolute_error: 0.0155, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.0864, root_relative_squared_error: 0.173, scimark_benchmark: 874.7324,

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