Looks like the format already has formats for some popular models, including SVM, regression, NNs.
Unclear to me how anyone could prevent us from using the standard unless it were patented. Copyright only protects works of art, which would include specific PMML files, but not the format. One thing I noticed is that open source projects are allowed to take part in the PMML process for free... My interpretation of PMML is that it represents a model. As others have mentioned, prediction models (e.g. classification, regression; not clustering) basically have two parts: (1) learning, where the training data is used to train (optimize parameters for) the model, (2) prediction, where values are assigned to data points (documents/genes/etc.) based on the model. In some cases (e.g. Naive Bayes, kNN), the "learning" is virtually non-existent and simply involves transforming the training data into a form that makes prediction easy/efficient. In other cases (e.g. SVM, ordinal regression, NN, non-naive Bayesian Network), learning involves non-trivial optimization, often requiring much more memory & computation than that of prediction, and there is value in being able to "save" a model for use elsewhere. The format is, of course, algorithm specific, so it's probably best to consider writing a PMML on an algorithm-by-algorithm basis... Jason
