In the previous post I explained how to create a hexagonal heatmap. For example to use as output for a self organizing map. I like to create rather large maps with a lot of hexagons if I have enough data. It gives the idea of a high resolution. In that case it’s very useful to divide the entire map into a manageable number of higher level segments.
In my previous post I spoke a bit about a program I wrote in R that helps me perform self organizing map (SOM) analyses and create heatmaps. From the cleaned data file all the way to the visualization and analysis of the heatmaps.
I’ve been using self organizing maps (or SOM) to analyse client data for more than a year now. In the beginning I tried some commercial software, but I did not like the fact that it was too easy to just randomly click some buttons and a map showed up. I wanted to know what was happening under the hood.
Even though R has been my favorite language to program in since a few months, one thing it is not designed to do is make your plots look anywhere near good. With this I mean that those plots are not the stuff I can just save and put into a client presentation.