Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL252

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL252

Task 93335 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL252 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-CHEMBL252
0 likes - 0 downloads - 0 reach - mean_absolute_error: 10.7497, mean_prior_absolute_error: 1.2329, number_of_instances: 1487, relative_absolute_error: 8.7189, root_mean_prior_squared_error: 1.4928, root_mean_squared_error: 46.112, root_relative_squared_error: 30.8898,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL252
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.867, mean_prior_absolute_error: 1.2329, number_of_instances: 1487, relative_absolute_error: 0.7032, root_mean_prior_squared_error: 1.4928, root_mean_squared_error: 1.1058, root_relative_squared_error: 0.7408,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL252
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.6392, mean_prior_absolute_error: 1.2329, number_of_instances: 1487, relative_absolute_error: 0.5185, root_mean_prior_squared_error: 1.4928, root_mean_squared_error: 0.8643, root_relative_squared_error: 0.579,

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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-CHEMBL252 (7)
    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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