There's been some discussion on the kaggle forums and on a few blogs about various ways to parallelize random forests, so I thought I'd add my thoughts on the issue.Here's my version of the 'parRF' function, which is based on the elegant version in the...

I've been playing around lately with the stock market data available from google finance, through quantmod in R. Here's a function I've written (which depends on the R Data Science Toolkit), to pull news stories related to a stock from google, parse t...

The Kaggle Don't Overfit competition is over, and I took 11th place! Additionally, I tied with tks for contributing the most to the forum, so thanks to everyone who voted for me! I voted for tks, and I'm very happy to share the prize with him, as most...

Now that we've got the data we need into R, it is very easy to fit a model using the caret package. Caret's workhorse function is called 'train,' and it allows you to fit a wide variety of models using the same syntax. Furthermore, many models have '...

Kaggle is a site for participating in predictive analytics competitions. It is also a great resource for learning how to build powerful predictive models, and the Overfitting competition provides a good introduction to the common tools used by a predic...

This is an example piece of code for the Overfitting competition at kaggle.com. This method has an AUC score of ~.91, which is currently good enough for about 38th place on the leaderboard. If you read the completion forums closely, you will find code...

This blog will show you how to build tools to survive in the modern world. I will focus on statistics and machine learning, because that's where my strengths lie, but sometime we may find ourselves veering far off course.My primary interest lies in us...