Task
Supervised Regression on cholesterol

Supervised Regression on cholesterol

Task 2295 Supervised Regression cholesterol 175 runs submitted
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Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 46.7045, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.188, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 59.9368, root_relative_squared_error: 1.1595,
Victorien Fandos 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... r=sklearn.svm._classes.SVR)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_prior_absolute_error: 39.3139, number_of_instances: 303, root_mean_prior_squared_error: 51.6914,
Victorien Fandos 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ession.KNeighborsRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_prior_absolute_error: 39.3139, number_of_instances: 303, root_mean_prior_squared_error: 51.6914,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 45.7754, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1644, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 59.3861, root_relative_squared_error: 1.1489,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.4bb97e7b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 46.1839, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1747, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 58.6393, root_relative_squared_error: 1.1344,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 44.3078, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.127, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 57.6023, root_relative_squared_error: 1.1144,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 102.9163, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 2.6178, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 147.0281, root_relative_squared_error: 2.8443,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.6284, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1097, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 56.8712, root_relative_squared_error: 1.1002,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.4bb97e7b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 40.9917, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0427, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 53.8119, root_relative_squared_error: 1.041,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.4bb97e7b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 41.0204, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0434, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.3348, root_relative_squared_error: 1.0705,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.4bb97e7b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.2556, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1003, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.6863, root_relative_squared_error: 1.0773,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.e88dfaf8998b5af(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.4371, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2575, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 65.7143, root_relative_squared_error: 1.2713,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.cea38ff1bee9c023(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 47.5881, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2105, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.7465, root_relative_squared_error: 1.2332,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.afabbd5fc39f30c1(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 47.4166, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2061, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.439, root_relative_squared_error: 1.2273,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 44.0509, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1205, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 57.9225, root_relative_squared_error: 1.1205,
Dragos Serban 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.8623, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1157, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 56.5306, root_relative_squared_error: 1.0936,
Dragos Serban 5 years ago
ran flow torch.nn.modules.container.Sequential.2c54586afd2ef685(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.7015, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2388, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.7873, root_relative_squared_error: 1.2533,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.bcd4e4eef3744c88(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.0363, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2473, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 65.3439, root_relative_squared_error: 1.2641,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.8215, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1147, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 57.2302, root_relative_squared_error: 1.1072,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.2309, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0996, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 57.5702, root_relative_squared_error: 1.1137,
Adrian-Stefan Mares 5 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.abab5292(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 44.7605, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1385, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 58.4481, root_relative_squared_error: 1.1307,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.e61660bb329d3407(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.453, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2325, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.942, root_relative_squared_error: 1.2563,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.d52b010daee34d1f(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 122.8904, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 3.1259, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 151.5614, root_relative_squared_error: 2.932,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.7e94579ad5a67d55(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 47.493, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.208, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.6887, root_relative_squared_error: 1.2321,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.484a8d8fee0bd5eb(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 47.0153, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1959, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.2086, root_relative_squared_error: 1.2228,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.90431c9af1f27d3d(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 40.7606, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0368, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.1652, root_relative_squared_error: 1.0672,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.21b39e8238057762(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 41.5142, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.056, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.6583, root_relative_squared_error: 1.0767,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.caaaf000c0d7266e(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.0392, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2219, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.0785, root_relative_squared_error: 1.2396,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.a5ea5c85df55e261(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 42.2168, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0738, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.97, root_relative_squared_error: 1.0828,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.f85cabaef09660ff(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 41.6913, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0605, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 55.4109, root_relative_squared_error: 1.072,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.82fbc60aa505f7fa(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.6908, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2385, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.8438, root_relative_squared_error: 1.2544,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.729a7069263fa6d5(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.17, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2253, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.1977, root_relative_squared_error: 1.2419,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.b8d6ae53e237215e(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.5178, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2595, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.6288, root_relative_squared_error: 1.2309,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.ee311f481dcb1f2c(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 40.5117, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0305, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 54.3928, root_relative_squared_error: 1.0523,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.68e5f33799ebe4b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.1562, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2504, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 65.82, root_relative_squared_error: 1.2733,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.bdf8a719b76476a7(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 178.6745, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 4.5448, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 190.9436, root_relative_squared_error: 3.6939,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.729a7069263fa6d5(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 46.747, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1891, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 62.7597, root_relative_squared_error: 1.2141,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.4af1d9dea0629591(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 47.1103, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.1983, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 62.9042, root_relative_squared_error: 1.2169,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.77c37292b030e991(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.0748, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2483, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 63.7676, root_relative_squared_error: 1.2336,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.f3559737fe837795(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 49.7763, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2661, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 65.4624, root_relative_squared_error: 1.2664,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.ef738e3ade38e6e4(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 182.007, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 4.6296, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 202.1232, root_relative_squared_error: 3.9102,
Adrian-Stefan Mares 5 years ago
ran flow torch.nn.modules.container.Sequential.b0b8a2df831102a(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.2871, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2282, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.6399, root_relative_squared_error: 1.2505,
Prabhant Singh 4 years ago
ran flow torch.nn.modules.container.Sequential.463f77fdacfeba1b(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 48.7199, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.2393, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 64.7734, root_relative_squared_error: 1.2531,
Prabhant Singh 4 years ago
ran flow torch.nn.modules.container.Sequential.e661c6d4bfeb5869(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 42.7599, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0877, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 54.096, root_relative_squared_error: 1.0465,
Prabhant Singh 4 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.d2a63ca2(2) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 43.1482, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0975, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 57.4551, root_relative_squared_error: 1.1115,
Prabhant Singh 4 years ago
ran flow mxnet.gluon.nn.basic_layers.HybridSequential.8150bebd(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 42.7405, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1.0872, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 56.994, root_relative_squared_error: 1.1026,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 7151350438.6204, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 181904060.8293, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 9525887890.3001, root_relative_squared_error: 184283782.1668,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 7627777678918, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 194022618078.57, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 8371385969492.8, root_relative_squared_error: 161949278240.71,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4266128337289.4, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 108514619054.48, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5053386026118.4, root_relative_squared_error: 97760660251.957,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 7260207881861.5, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 184672993934.62, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 8014999963784.2, root_relative_squared_error: 155054785905.76,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3732888385404.3, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 94950955313.366, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4392893850288.7, root_relative_squared_error: 84983059081.844,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 2027452237535.3, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 51570930317.367, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 2108595323916.7, root_relative_squared_error: 40791989767.823,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4434180229.3858, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 112789241.2905, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5676874781.9453, root_relative_squared_error: 109822408.9714,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4523503029755.1, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 115061284906.76, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4985277069301.7, root_relative_squared_error: 96443053294.352,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4010696703780.8, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 102017377477.76, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4805241907505.4, root_relative_squared_error: 92960169502.217,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 31660484190182, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 805326307450.24, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 34289531543528, root_relative_squared_error: 663350716945.02,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1.3432701018087E+14, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 3416785240869.3, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 1.4642272629882E+14, root_relative_squared_error: 2832631887783.9,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 15815181204.12, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 402280060.0352, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 25396618840.013, root_relative_squared_error: 491312203.9628,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 13031663238.954, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 331477597.5352, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 17417581858.674, root_relative_squared_error: 336953142.6445,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3727286649285.7, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 94808467743.165, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4179571006183.3, root_relative_squared_error: 80856205922.637,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 7780970166.0275, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 197919271.6873, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 10538819373.238, root_relative_squared_error: 203879524.5166,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 957756720829.07, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 24361809465.318, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 1152860753634.6, root_relative_squared_error: 22302754602.829,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3589241531200.7, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 91297107508.08, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4170117686522.6, root_relative_squared_error: 80673326014.626,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 11426576114.556, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 290650082.7296, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 16207922014.089, root_relative_squared_error: 313551576.9466,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 59894907126.375, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 1523506213.6578, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 82787447476, root_relative_squared_error: 1601570805.0003,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 6644271535.6064, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 169005837.9817, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 8954621763.5024, root_relative_squared_error: 173232310.2534,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3761165414333.3, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 95670218959.377, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 3925183694757.4, root_relative_squared_error: 75934937015.775,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4543913838982.4, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 115580460846.35, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5236553694777.8, root_relative_squared_error: 101304144191.72,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 83231550967529, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 2117104628008.9, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 88101157320498, root_relative_squared_error: 1704367579301.9,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1660151627678.3, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 42228153306.015, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 2106278851502.2, root_relative_squared_error: 40747176276.132,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9585221576969.2, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 243812793648.52, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 10356276280204, root_relative_squared_error: 200348123351.67,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3455207832.139, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 87887783.0236, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4532427361.7985, root_relative_squared_error: 87682415.1457,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4022427976389.4, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 102315777918.98, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4711031322223.3, root_relative_squared_error: 91137611523.804,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3508615170729.6, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 89246269347.447, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 3775038614525.8, root_relative_squared_error: 73030294049.423,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 5975933315.4909, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 152005771.0307, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 7901650326.7732, root_relative_squared_error: 152861971.9596,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8874463711.9536, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 225733726.9013, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 13887800513.775, root_relative_squared_error: 268667491.5902,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 10303949196.5, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 262094581.6472, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 14393400152.257, root_relative_squared_error: 278448607.5045,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 8631765812044.4, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 219560384687.5, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 9030042873457.8, root_relative_squared_error: 174691375020.64,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 38269484701379, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 973434980256.63, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 41666206688638, root_relative_squared_error: 806056741959.32,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3541313464321.2, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 90077993710.216, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4087071994925.2, root_relative_squared_error: 79066759328.511,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9973940566.5323, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 253700375.4878, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 14076849756.132, root_relative_squared_error: 272324757.9572,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 658774854276.46, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 16756810086.943, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 994723117617.55, root_relative_squared_error: 19243491046.116,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4899437242.306, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 124623669.0263, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 7312081378.383, root_relative_squared_error: 141456421.4315,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 6385485296.7007, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 162423267.578, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 10238332804.053, root_relative_squared_error: 198066438.9442,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3375317569372, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 85855668482.075, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4089148260777.3, root_relative_squared_error: 79106925886.045,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 5434541862820.2, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 138234763081.29, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 6044703958102.1, root_relative_squared_error: 116938276022.74,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4788017332756, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 121789556199.9, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5038126514821.1, root_relative_squared_error: 97465456226.014,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 5868714739.6686, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 149278524.6867, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 10180107747.005, root_relative_squared_error: 196940041.7145,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 11073745100.056, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 281675359.0218, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 16280182147.583, root_relative_squared_error: 314949490.8055,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 2.4722999830221E+14, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 6288622133119.2, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 2.775981142387E+14, root_relative_squared_error: 5370295242122.8,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 6962538827.8192, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 177101387.6795, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 11330301019.619, root_relative_squared_error: 219191192.3622,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 3254468565294.9, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 82781714160.095, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 3602297595411.3, root_relative_squared_error: 69688519644.312,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 5294266190993.1, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 134666665760.38, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5853972790069.4, root_relative_squared_error: 113248471835.78,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 220643841694.49, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 5612368061.9061, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 541681272663.96, root_relative_squared_error: 10479135887.908,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4806083971294.2, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 122249105056.27, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5216707624042.6, root_relative_squared_error: 100920210534.47,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4607969556241.6, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 117209802771.17, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4844891791315.5, root_relative_squared_error: 93727219317.955,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4490882430431, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 114231536800.49, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 4625326253389, root_relative_squared_error: 89479597654.91,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 4722264798823.5, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 120117053497.81, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 5195293097830.7, root_relative_squared_error: 100505934203.58,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 6873440728.8756, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 174835059.6413, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 12868203134.069, root_relative_squared_error: 248942793.632,
Christian Geißler 5 years ago
ran flow sklearn.pipeline.Pipeline(impu ... stic_gradient.SGDRegressor)(1) on task Supervised Regression on data set cholesterol
0 likes - 0 downloads - 0 reach - mean_absolute_error: 5965871837075.2, mean_prior_absolute_error: 39.3139, number_of_instances: 303, relative_absolute_error: 151749844014.17, root_mean_prior_squared_error: 51.6914, root_mean_squared_error: 6170193692742.5, root_relative_squared_error: 119365947142.63,

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

Given a dataset with a numeric target and a set of train/test splits, e.g. generated by a cross-validation procedure, train a model and return the predictions of that model.

Given inputs

estimation_procedure 10-fold Crossvalidation
evaluation_measures mean_absolute_error
source_data cholesterol (1)
target_feature chol

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

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