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I've been able to create some successful R ML models using some of the popular machine learning algorithms. However, I'm not sure how to implement the model where the end users (technically challenged) can utilize the model with a few button clicks. They prefer a web or a traditional application interface.

Can someone point me in the right direction? Thank you very much in advance.

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I think this question is more suited for StackOverflow.

Having said that, Java would be an obvious choice, especially if what you have in mind is a web interface.

You can have a look at JRI, which allows you to run R inside Java applications as a single thread. Basically, you can write Javascript UI code on the client side, and on the server side you can have some Java code wrapping around your R solutions.

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If you want to deploy machine learning models there are many alternatives such as python or RapidMiner.

However, if you want to use your R model I suggest the following options:

  • Use the package RServe (http://rforge.net/Rserve/doc.html) it seems pretty interesting and they claim to deploy R models on Java.
  • Use the PMML model language. This PMML language allows R users to translate their models into XML-like files so that other languages (such as Java) can interpret the characteristic of the model.

If your model is a standard tree or SVM I recommend to use PMML model. Otherwise, consider RServe.

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I was successfully able to deploy/expose a xgboost model through rPLumber. It is relatively easy.

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There is a library to create web application with R http://www.rstudio.com/shiny/

I think that for a real world application R is not the best choice. I think that python could be a better choice.

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  • $\begingroup$ are there any other tools? $\endgroup$ – dormantroot May 25 '14 at 20:56
  • $\begingroup$ This is something that should be easy to start. Theoretically you can link R to every programming language and use it to build a graphic interface $\endgroup$ – Donbeo May 25 '14 at 21:38

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