Excerpts from Nina Jeliazkova's message of Fri Dec 04 12:39:56 +0100 2009:
> > I use the following workflow:
> >
> > POST /descriptor_calculation training_dataset                                    # creates feature_dataset
> > POST /algorithm              training_dataset feature_dataset # creates model
> > POST /model                  compound_uri                     # creates prediction
> > or
> > POST /model                  prediction_dataset               # creates dataset with predictions
> >
> > This is fairly straightforward and allows you to reuse/exchange descriptors.
> >   
> Yes, but straightforward implementation duplicates information
> (training/feature datasets are not very much different).  

No, training and feature datasets are disjunct in my case. This allows
me e.g. to quickly create lazar models with different types of
descriptors and compare the results with other algorithms.

Best regards,
Christoph