[OTDev] SuperAlgorithm/Model Examples
Christoph Helma helma at in-silico.deTue Jan 4 12:55:15 CET 2011
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Dear all, During our last meeting I promised to post an example of our SuperAlgorithm/Model implementations: SuperAlgorithm (incorporates feature mining): - (text/uri-list) POST '/algorithm/lazar/?' Create a lazar prediction model Parameters: (String) dataset_uri — Training dataset URI (optional, String) prediction_feature — URI of the feature to be predicted (optional, String) feature_generation_uri — URI of the feature generation algorithm (optional, String) - — further parameters for the feature generation service Returns: (text/uri-list) — Task URI Right now all additional parameters are passed to the feature_generation service - for a generic API we would need a mechanism to split parameters among sub-algorithms (e.g. feature calculation, feature selection, model learning). The completed task returns a lazar model, which I would consider a SuperModel (integrates feature generation for the query compound(s)): - (text/uri-list) POST '/model/:id/?' Make a lazar prediction. Predicts either a single compound or all compounds from a dataset Parameters: (optional, String) dataset_uri — URI of the dataset to be predicted (optional, String) compound_uri — URI of the compound to be predicted (optional, Header) Accept — Content-type of prediction, can be either `application/rdf+xml or application/x-yaml` Returns: (text/uri-list) — URI of prediction task (dataset prediction) or prediction dataset (compound prediction) IMHO SuperModels should wrap everything that is needed to predict chemical structures (application of feature generation algorithms, sub-models and consensus algorithms for consensus predictions, ...) into a single object. They should accept (and need) only chemical structures as input parameters. Best wishes for the new year! Christoph
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