Using R Language for Decision Modeling

The R is a highly popular free programming language that provides a powerful array of development tools in the numeric analysis and machine learning spaces. With growing popularity of business analytics in general, the popularity of the R language can only be expected to grow. Like any language, R has both pros and cons that developers should know. 

It was natural that when we published the first pure Predictive Analytics challenge “Patient Diagnosis Decision” the first (and so far the only) solution was submitted using the R language.  Since then its author Dr. Riccardo Hertel submitted several more R-based solutions for pure decision modeling  challenges. Today we received his solution for the Sep-2015 Challenge with this kind email:

 “Dear members of the Decision Management Community,
Please find attached my suggested solution for the September 2015 Challenge “Collections of Cars”. Thank you very much for proposing these stimulating challenges. I would like to take this opportunity to express my gratitude for publishing my previous submission of the August 2015 Challenge that I sent you a few days ago. It is an honor for me to be represented on your website, and I hope that you will find this contribution to your new Challenge useful.
Best regards, Dr. Riccardo Hertel”

Dr. Hertel is effectively using different  packages that accompany the R language to provide quite elegant modeling facilities. While they are essentially different from commonly used DMN-style decisioning tools, they not only show an alternative approach but more importantly could be used for easy integration between business rules and predictive analytics technologies. Here is the list of provided R-based decision models:

This entry was posted in Business Analytics, Challenges, Decision Models, Trends. Bookmark the permalink.

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