Machine Learning Examples in R

February 12, 2012
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(This article was first published on Shifting sands, and kindly contributed to R-bloggers)

This is a post that has been a long time in the making. Following on from the excellent Stanford Machine Learning Course I have made examples of the main algorithms covered in R.

We have Linear Regression



Followed by Neural Networks
And Support Vector Machines



One remaining item is Logistic Regression, I am yet to find a library in R that behaves as I want, so that will come at some future date. I've been sitting on this post for ages and got sick of waiting. As an aside I find the documentation in R to be variable at best, which can make it somewhat of a pain to work with. When it is good, yes it can be very good but often it is quite poor ...

R is great for data analysis and exploration, but I have found myself moving back to python for many more mundane tasks.

Anyway for those interested in the code, I have put it on Github. The data is from an exercise in the Stanford course, and by tweaking the parameters I really got a good feel for how the various algorithms work in practise.

Once I finish my backtesting engine I will probably put it up on Github as well, and then I can start digging into the applications of ML techniques for trading systems.

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