Task
Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1901

Supervised Regression on QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1901

Task 94841 Supervised Regression QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1901 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-CHEMBL1901
0 likes - 0 downloads - 0 reach - mean_absolute_error: 9.1188, mean_prior_absolute_error: 1.3234, number_of_instances: 455, relative_absolute_error: 6.8904, root_mean_prior_squared_error: 1.5837, root_mean_squared_error: 27.0054, root_relative_squared_error: 17.0526,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.rpart(3) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1901
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.6325, mean_prior_absolute_error: 1.3234, number_of_instances: 455, relative_absolute_error: 0.4779, root_mean_prior_squared_error: 1.5837, root_mean_squared_error: 0.9622, root_relative_squared_error: 0.6076,
Noureddin Sadawi 8 years ago
ran flow mlr.regr.ksvm(2) on task Supervised Regression on data set QSAR-DATASET-FOR-DRUG-TARGET-CHEMBL1901
0 likes - 0 downloads - 0 reach - mean_absolute_error: 0.5533, mean_prior_absolute_error: 1.3234, number_of_instances: 455, relative_absolute_error: 0.4181, root_mean_prior_squared_error: 1.5837, root_mean_squared_error: 0.8396, root_relative_squared_error: 0.5302,

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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-CHEMBL1901 (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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