Self-organizing map - visualizing of heatmaps

Over the past decade, there has been exponential growth in information. Gaining new knowledge from such databases is difficult, costly, and time-consuming if done manually. It may even be impossible when the data exceeds certain limits of size and complexity. As a result, the automated analysis and visualization of massive multidimensional datasets have been the focus of much scientific research over the last few years. The principal objective of this analysis and visualization is to find regularities and relationships in the data, thereby gaining access to hidden and potentially useful knowledge. A self-organizing map (SOM) is an unsupervised neural network algorithm that projects high-dimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map.

How to do it...

Let's get into the details.

Step 1 - exploring data

The...