So, the inevitable question now arises: how do these things work?
In a nutshell, we have neurons on the grid; gradually, via iterations, they adapt themselves to the shape of our data (in our example, shown in the following image on the left-hand side in the Points panel). Let's talk a bit more about the iterative process itself.
- The first step is to randomly position data on the grid. We will randomly be placing our grid's neurons in our data space, as follows:
- The second step is where our algorithm will select a single data point.
- In the third step, we need to find the neuron (data point) that is closest to the ...