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machine learning

This category contains 5 posts

Buster – a new R package for bagging hierarchical clustering

I recently found myself a bit stuck. I needed to cluster some data. The distances between the data points were not representable in Euclidean space so I had to use hierarchical clustering. But then I wanted stable clusters that would retain their shape as I updated the data set with new observations. This I could … Continue reading

Freehand Diagrams with Adobe Ideas

Freehand diagrams have two big virtues: they are quick and they are unconstrained. I used to use a notebook (see What are degrees of freedom) but recently I got an ipad and then I found Adobe Ideas. It’s completely free and has just the right level of complexity for getting ideas down fast. It takes … Continue reading

Deploying your Mahout application as a webapp on Openshift

Openshift (a cloud computing platform from Redhat) does not at present support Hadoop so this is not a route to go down if you have the kind of data that requires map reduce. However it’s not a bad option if you’re just playing with Mahout (see the previous post) and would like to share what … Continue reading

Book Recommendations from Beyond the Grave: A Mahout Example

In H P Lovecraft’s The Case of Charles Dexter Ward the villainous Curwen, having taken possession of the body of Charles Dexter Ward, uses a combination of chemistry and black magic to bring back from the dead the wisest people who have ever lived. He then tortures them for their secrets. Resurrection of the dead … Continue reading

Mahout for R Users

I have a few posts coming up on Apache Mahout so I thought it might be useful to share some notes. I came at it as primarily an R coder with some very rusty Java and C++ somewhere in the back of my head so that will be my point of reference. I’ve also included … Continue reading

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