[OTDev] Fwd: Predicted variables and confidence --- was: [OTP] Lazar models
Martin Guetlein martin.guetlein at googlemail.comFri May 27 10:19:27 CEST 2011
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On Thu, May 26, 2011 at 11:26 PM, Christoph Helma <helma at in-silico.ch>wrote: > > > Dear Christoph, > > > > On 26 May 2011 13:40, Christoph Helma <helma at in-silico.ch> wrote: > > > > > Dear Nina, Martin, All, > > > > > > It seems yesterdays reply was not delivered to the list. > > > > > > > What about combining both solutions? Features could be in the > dataset, > > > as > > > > in IST services, or as separate resources, but additionally models > > > provide > > > > list of predicted variables via /model/id/predicted ? This way there > > > will > > > > be still no need of a separate feature service for you. > > > > > > Problem is that the prediction feature URIs (of the form > > > /dataset/:id/feature/prediction/:name/{value|confidence}) are built on > > > top of the dataset URI, which I cannot know in advance. > > > > > > I wonder, why predicted features URIs should be dataset dependent, > rather > > than model dependent ? > > > > Semantically, the same variable is predicted by a given model, regardless > of > > which dataset is submitted for the model. Dataset dependent URIs for > > predicted variables may introduce confusion if somebody stores triples > from > > several datasets in a same triple storage (which is at the end the > intended > > use of all the RDF serialization). Am I wrong? > > > > > > > For this reason > > > new features are created for each prediction. Any ideas how to solve > > > that without a dedicated feature service? Or would it be easier to > > > implement a feature service (or use AMBITs) for this purpose (what > about > > > A+A)? > > > > > > > Actually in the AA protected version we hide features and compounds > inside > > models or datasets, at least this is what appears externally, internally > it > > is the same service-global list of features. In case of models , the > > features are relative to the model , e.g. /model/1/predicted have the > same > > policy as /model/1 . > > Stupid me! I can save the predicted feature in the model and reference > that from the prediction dataset, not the other way round. This is how I > have implemented it now in the development branch (you can see it in the > last models at ot-dev.in-silico.ch). > > @Martin: Can you adjust the validation service - I get 2 errors from the > tests where validation expects the old representation. > > @Micha, Andi: Nightly validation tests at the integration server will > fail for this reason. > Great, I adjusted the validation, the tests are running and things are a bit easier. Best regards, Martin P.S.: The validation service has become a bit more strict on determining weather a model performs prediction or regression: The rdf-type of the predicted feature has to be set to numeric or nominal (nominal preferred if both are set). > > Best regards, > Christoph > _______________________________________________ > Development mailing list > Development at opentox.org > http://www.opentox.org/mailman/listinfo/development > -- Dipl-Inf. Martin Gütlein Phone: +49 (0)761 203 8442 (office) +49 (0)177 623 9499 (mobile) Email: guetlein at informatik.uni-freiburg.de
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