Helping R Stay in the Lead by Deploying Models with PFA

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We introduce a new language for deploying analytic models into products, services and operational systems called the Portable Format for Analytics (PFA). PFA is an example of what is sometimes called a model interchange format, a standard and domain specific language for describing analytic models that is independent of specific tools, applications or systems. Model interchange formats allow one application (the model producer) to export models and another application (the model consumer or scoring engine) to import models. The core idea behind PFA is to support the safe execution of statistical functions, mathematical functions, and machine learning algorithms and their compositions within a safe execution environment. With this approach, the common analytic models used in data science can be implemented, as well as the data transformations and data aggregations required for pre- and post-processing data. We will discuss the deployment of models developed in R using PFA, why PFA is strategically important for the R community, and the current state of R libraries for PFA exporting and manipulation of models developed in R.





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The Discussion

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    PFA at concept is really great and seems quite flexible compared to PMML. I would really appreciate if you share details as to how deployment of PFA model works in production deployment(basically scoring). Do I need some third party tools like ADAPA scoring to make it work.

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