There are many classifiers available today, including SVM and ANN, each with their own strengths and assumptions. Performance varies depending on the situation and how well suited each classifier is to a particular set of conditions. I don't think it is possible to claim that one classifier is superior in every domain or case. Much of the success of the SAS Enterprise Miner is due to the wide range of models and algorithms that it provides. You can explore and compare many different approaches with it before deciding on the best one. That advantage is the motivation for the recent addition of new features like the Formula Depot and the Model Comparison platform to JMP Pro.
As Dan explained in the comments about the original blog post about the JMP to R Add-in Builder, this project, while impressive as far as it goes, was not complete before the summer intern, Julia, left SAS and returned to school.
Caveat: JMP scripts, add-ins, and applications found in the JMP Community are wonderful extensions to JMP but they are not supported, even the ones developed by staff. They are provided for your use 'as is.'
If you cannot wait for the next version of this add-in (no promises!) then you might see Help > Scripting Guide for information and examples about scripting JMP to work with R. If you write R scripts now then you might be able to use JSL. It is straight-forward to connect to R, submit R scripts, and receive R results with JMP. The add-in is convenient but not necessary for this connection.