Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4777

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4777

Task 94328 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4777 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-CHEMBL4777
0 likes - 0 downloads - 0 reach - mean_absolute_error: 2261.615, mean_prior_absolute_error: 1.1843, number_of_instances: 1030, relative_absolute_error: 1909.7024, root_mean_prior_squared_error: 1.3988, root_mean_squared_error: 7889.0967, root_relative_squared_error: 5639.7462,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4777
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.646, mean_prior_absolute_error: 1.1843, number_of_instances: 1030, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 1.3988, root_mean_squared_error: 0.8965, root_relative_squared_error: 0.6409,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL4777
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.5079, mean_prior_absolute_error: 1.1843, number_of_instances: 1030, relative_absolute_error: 0.4289, root_mean_prior_squared_error: 1.3988, root_mean_squared_error: 0.6858, root_relative_squared_error: 0.4903,

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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-CHEMBL4777 (8)
    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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