Task
Supervised Data Stream Classification on BNG(anneal,1000,5)

Supervised Data Stream Classification on BNG(anneal,1000,5)

Task 7330 Supervised Data Stream Classification BNG(anneal,1000,5) 10 runs submitted
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Jan van Rijn 10 years ago
ran flow moa.LeveragingBag_kNN(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9655, f_measure: 0.8682, kappa: 0.6603, kb_relative_information_score: 864392.0704, mean_absolute_error: 0.0497, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.8871, predictive_accuracy: 0.8859, prior_entropy: 2.585, recall: 0.8859, relative_absolute_error: 0.1788, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1638, root_relative_squared_error: 0.4396,
Jan van Rijn 10 years ago
ran flow moa.OzaBoostAdwin_HoeffdingTree(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9669, f_measure: 0.894, kappa: 0.7359, kb_relative_information_score: 800130.4514, mean_absolute_error: 0.0847, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.893, predictive_accuracy: 0.9011, prior_entropy: 2.585, recall: 0.9011, relative_absolute_error: 0.3051, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1741, root_relative_squared_error: 0.4672,
Jan van Rijn 10 years ago
ran flow moa.RuleClassifier(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7798, f_measure: 0.7273, kappa: 0.2433, kb_relative_information_score: 702056.1323, mean_absolute_error: 0.106, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.7289, predictive_accuracy: 0.7793, prior_entropy: 2.585, recall: 0.7793, relative_absolute_error: 0.3818, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2381, root_relative_squared_error: 0.6388,
Jan van Rijn 10 years ago
ran flow moa.OzaBoost_HoeffdingTree(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9359, f_measure: 0.8551, kappa: 0.633, kb_relative_information_score: 737192.4816, mean_absolute_error: 0.108, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.8516, predictive_accuracy: 0.8634, prior_entropy: 2.585, recall: 0.8634, relative_absolute_error: 0.3889, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.199, root_relative_squared_error: 0.534,
Jan van Rijn 10 years ago
ran flow moa.OzaBagAdwin_HoeffdingTree(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9877, f_measure: 0.9411, kappa: 0.8543, kb_relative_information_score: 905328.3931, mean_absolute_error: 0.0393, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.9404, predictive_accuracy: 0.943, prior_entropy: 2.585, recall: 0.943, relative_absolute_error: 0.1416, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1223, root_relative_squared_error: 0.3281,
Jan van Rijn 10 years ago
ran flow moa.LeveragingBag_HoeffdingTree(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9881, f_measure: 0.9431, kappa: 0.8599, kb_relative_information_score: 917177.2458, mean_absolute_error: 0.0336, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.9427, predictive_accuracy: 0.9452, prior_entropy: 2.585, recall: 0.9452, relative_absolute_error: 0.121, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1185, root_relative_squared_error: 0.3178,
Jan van Rijn 10 years ago
ran flow moa.kNN(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.964, f_measure: 0.8685, kappa: 0.6619, kb_relative_information_score: 864865.2804, mean_absolute_error: 0.0495, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.8873, predictive_accuracy: 0.8863, prior_entropy: 2.585, recall: 0.8863, relative_absolute_error: 0.1782, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.1637, root_relative_squared_error: 0.4393,
Jan van Rijn 10 years ago
ran flow moa.HoeffdingTree(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.85, f_measure: 0.7995, kappa: 0.4851, kb_relative_information_score: 750452.422, mean_absolute_error: 0.0888, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.7957, predictive_accuracy: 0.8084, prior_entropy: 2.585, recall: 0.8084, relative_absolute_error: 0.3195, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2247, root_relative_squared_error: 0.603,
Jan van Rijn 10 years ago
ran flow moa.SGD(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.022, kappa: -0.0002, kb_relative_information_score: 18249.825, mean_absolute_error: 0.297, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.0123, predictive_accuracy: 0.1089, prior_entropy: 2.585, recall: 0.1089, relative_absolute_error: 1.0693, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.545, root_relative_squared_error: 1.4624,
Jan van Rijn 10 years ago
ran flow moa.NaiveBayes(1) on task Supervised Data Stream Classification on data set BNG(anneal,1000,5)
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7666, f_measure: 0.6956, kappa: 0.2545, kb_relative_information_score: 626854.5014, mean_absolute_error: 0.1281, mean_prior_absolute_error: 0.2778, number_of_instances: 1000000, precision: 0.702, predictive_accuracy: 0.6905, prior_entropy: 2.585, recall: 0.6905, relative_absolute_error: 0.4612, root_mean_prior_squared_error: 0.3727, root_mean_squared_error: 0.2685, root_relative_squared_error: 0.7205,

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    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 nominal target, various data samples of increasing size are defined. A model is build for each individual data sample; from this a learning curve can be drawn.

    Given inputs

    estimation_procedure Interleaved Test then Train
    source_data BNG(anneal,1000,5) (1)
    target_feature class

    Expected outputs

    evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
    predictions The desired output format Predictions (optional)

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