I’ve had a whole lot of fun writing a paper for the IEEE ICDM conference, which
is going to take place in Sydney, Australia, this year. The programming work
was there, I had some novel data sets to analyse and I came to some cool
conclusions using my homebrew algorithm which explicitly assumes spatial
autocorrelation in the data sets. I could also show that the algorithm produces
meaningless results when spatial autocorrelation does not exist.

It also implements a more or less standard hierarchical agglomerative
clustering procedure on spatial data — there just was no existing work which
fit the problem and the data set, so I had to create my own algorithm using a
straightforward and easily explainable divide-and-conquer approach. I hope that
my reviewers at the IEEE ICDM conference like the idea.

I’m still looking for an easily pronouncable acronym, maybe HACSAD-PA
will do: hierarchical agglomerative clustering for spatially autocorrelated
data from precision agriculture :-)

Oh, right, I’m using the vim blogit plugin to operate my wordpress blog via VIm — there’s nothing better than VIm and I use it for everything. I even tried to get it to cooperate with Matlab, but that effort got pointless when I switched to R, anyway.