Oct 09 02:03

K-means & correlation distance

Here's a useful observation related to the use of K-means together with the Pearson correlation distance (© Alex).

The standard K-means update step, where you update the cluster centers by taking the means of the corresponding points is technically not very appropriate in the case of the correlation distance d(x, y) = 1 - corr(x, y). The proper step would be to take the sum of the normalized points as the new cluster center:

c = sumi(xi/|xi|)

Nov 23 01:12

A Brief Introduction to Matrix Algebra

I made up a short guide on the basics of matrix algebra for the recent pattern analysis course to kinda help the catch-uppers.
Despite the fact that it did not seem to help a lot (it's probably too compressed for a beginner and too obvious for the one who knows), I still decided to make it into a more-or-less complete document, which maybe someday end up being useful.

The good point about it is that it summarizes about pretty much all of linear algebra that I, personally, know and find useful.

The PDF is available here.