Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111431

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111431

Task 95468 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111431 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-CHEMBL2111431
0 likes - 0 downloads - 0 reach - mean_absolute_error: 1.9077, mean_prior_absolute_error: 0.6764, number_of_instances: 95, relative_absolute_error: 2.8203, root_mean_prior_squared_error: 0.8048, root_mean_squared_error: 2.7697, root_relative_squared_error: 3.4416,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111431
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.701, mean_prior_absolute_error: 0.6764, number_of_instances: 95, relative_absolute_error: 1.0363, root_mean_prior_squared_error: 0.8048, root_mean_squared_error: 0.8624, root_relative_squared_error: 1.0716,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL2111431
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.6389, mean_prior_absolute_error: 0.6764, number_of_instances: 95, relative_absolute_error: 0.9445, root_mean_prior_squared_error: 0.8048, root_mean_squared_error: 0.7769, root_relative_squared_error: 0.9654,

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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-CHEMBL2111431 (3)
    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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