Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288

Task 108345 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288 3 runs submitted
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Noureddin Sadawi 8 years ago
ran flow mlr.regr.rsm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288
0 likes - 0 downloads - 0 reach - mean_absolute_error: 12.2341, mean_prior_absolute_error: 1.4329, number_of_instances: 537, relative_absolute_error: 8.538, root_mean_prior_squared_error: 1.6368, root_mean_squared_error: 36.4296, root_relative_squared_error: 22.2566,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.7023, mean_prior_absolute_error: 1.4329, number_of_instances: 537, relative_absolute_error: 0.4901, root_mean_prior_squared_error: 1.6368, root_mean_squared_error: 0.9348, root_relative_squared_error: 0.5711,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL288
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.5873, mean_prior_absolute_error: 1.4329, number_of_instances: 537, relative_absolute_error: 0.4099, root_mean_prior_squared_error: 1.6368, root_mean_squared_error: 0.8065, root_relative_squared_error: 0.4927,

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    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-CHEMBL288 (12)
    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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