Task
Supervised Regression on mbagrade

Supervised Regression on mbagrade

Task 2281 Supervised Regression mbagrade 7 runs submitted
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Tan Zheng 4 years ago
ran flow sklearn.neighbors._regression.KNeighborsRegressor(2) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_prior_absolute_error: 0.2571, number_of_instances: 61, root_mean_prior_squared_error: 0.3261,
Tan Zheng 4 years ago
ran flow sklearn.tree._classes.DecisionTreeRegressor(1) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_prior_absolute_error: 0.2571, number_of_instances: 61, root_mean_prior_squared_error: 0.3261,
Tan Zheng 4 years ago
ran flow sklearn.linear_model._base.LinearRegression(2) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_prior_absolute_error: 0.2571, number_of_instances: 61, root_mean_prior_squared_error: 0.3261,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart.dummied(1) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2559, mean_prior_absolute_error: 0.2571, number_of_instances: 61, relative_absolute_error: 0.9952, root_mean_prior_squared_error: 0.3261, root_mean_squared_error: 0.3377, root_relative_squared_error: 1.0357, usercpu_time_millis: 0.097, usercpu_time_millis_testing: 0.034, usercpu_time_millis_training: 0.063,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2559, mean_prior_absolute_error: 0.2571, number_of_instances: 61, relative_absolute_error: 0.9952, root_mean_prior_squared_error: 0.3261, root_mean_squared_error: 0.3377, root_relative_squared_error: 1.0357, usercpu_time_millis: 0.043, usercpu_time_millis_testing: 0.012, usercpu_time_millis_training: 0.031,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart.dummied(1) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2559, mean_prior_absolute_error: 0.2571, number_of_instances: 61, relative_absolute_error: 0.9952, root_mean_prior_squared_error: 0.3261, root_mean_squared_error: 0.3377, root_relative_squared_error: 1.0357, usercpu_time_millis: 0.129, usercpu_time_millis_testing: 0.027, usercpu_time_millis_training: 0.102,
Heidi Seibold 7 years ago
ran flow mlr.regr.rpart(5) on task Supervised Regression on data set mbagrade
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2559, mean_prior_absolute_error: 0.2571, number_of_instances: 61, relative_absolute_error: 0.9952, root_mean_prior_squared_error: 0.3261, root_mean_squared_error: 0.3377, root_relative_squared_error: 1.0357, usercpu_time_millis: 0.04, usercpu_time_millis_testing: 0.011, usercpu_time_millis_training: 0.029,

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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 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 mbagrade (1)
    target_feature grade_point_average

    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)

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