Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3946

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3946

Task 93977 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3946 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-CHEMBL3946
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.3667, mean_prior_absolute_error: 0.2363, number_of_instances: 12, relative_absolute_error: 1.5515, root_mean_prior_squared_error: 0.3005, root_mean_squared_error: 0.4648, root_relative_squared_error: 1.5468,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3946
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2611, mean_prior_absolute_error: 0.2363, number_of_instances: 12, relative_absolute_error: 1.1048, root_mean_prior_squared_error: 0.3005, root_mean_squared_error: 0.3286, root_relative_squared_error: 1.0936,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL3946
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.2903, mean_prior_absolute_error: 0.2363, number_of_instances: 12, relative_absolute_error: 1.2283, root_mean_prior_squared_error: 0.3005, root_mean_squared_error: 0.3576, root_relative_squared_error: 1.19,

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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-CHEMBL3946 (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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