Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151

Task 102003 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151 3 runs submitted
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Noureddin Sadawi 9 years ago
ran flow mlr.regr.rsm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1.9714, mean_prior_absolute_error: 1.3504, number_of_instances: 16, relative_absolute_error: 1.4599, root_mean_prior_squared_error: 1.6291, root_mean_squared_error: 2.7209, root_relative_squared_error: 1.6702,
Noureddin Sadawi 9 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1.4799, mean_prior_absolute_error: 1.3504, number_of_instances: 16, relative_absolute_error: 1.0959, root_mean_prior_squared_error: 1.6291, root_mean_squared_error: 1.7764, root_relative_squared_error: 1.0904,
Noureddin Sadawi 9 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1.4199, mean_prior_absolute_error: 1.3504, number_of_instances: 16, relative_absolute_error: 1.0515, root_mean_prior_squared_error: 1.6291, root_mean_squared_error: 1.6482, root_relative_squared_error: 1.0117,

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    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 Custom 10-fold Crossvalidation
    source_data QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2095151 (4)
    target_feature pXC50

    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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