R PMML Support: Data Transformations

R and PMML Export     R is becoming the tool of choice for many data scientists. It is no wonder that many commercial and open-source statistical tools are also embracing R. Predictive Models A set of robust predictive analytic techniques is but one set of tools available to data scientists in R. Another important set is the ability to export PMML for a host of predictive models.  By using the pmml package (version 1.2.33 or higher), users can export PMML from R for: Random Forest Models Neural Networks Clustering Models Cox Regression Models Linear and Logistic Regression Models Support Vector Machines Association Rules Generalized Linear Models Random Survival Forest Models Data Transformations And now, another R package extends this functionality by providing PMML export for data transformations. The new pmmlTransformations package has just made its way to CRAN (the Comprehensive R Archive Network).  Want to apply a Z-scoring normalization procedure to your continuous input variables before presenting them to a neural network? No problem. Use the pmmlTransformations package in conjunction with the pmml package (version 1.2.33 or higher) to export the entire process (pre-processing + model) into a PMML file.  To look at the package's documentation in CRAN, click HERE.

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