Dear All,
 In API 1.0 we accepted an XML schema for the representation of our
models. This XML is small and simple and contains all meta-information
about the model (user, id, name, tuning parameters, dataset uri) but no
information about the parameters of the trained model. I'm not sure if
this is a real problem or not since a client can use this model to
perform predictions without caring about these parameters but its very
easy to build such models and internally store a model in any file
format (serialized weka file, PMML, LibSVM DSD files, etc...). So do we
have to provide this PMML file?
  On the other hand, as Jorg mentioned, PMML files are widely accepted
in industry while others (including me) have reported difficulty in
building such models. Indeed, generating a PMML model is not
straightforward in some cases and I still can't figure out how can I
convert the LibSVM output into a PMML format (I'm talking about SVM
models). 
   So I'm wandering if we need to provide those models as PMML or if its
ok (at least for now), to provide our In-house XMLs for Model Object....

Any Suggestions/Objections/Alternative ideas/Proposals (SOAP)?

Best Regrads,
Pantelis