RStudio

RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

Self Organizing Map (SOM) - Neural Network

A self-organizing map (SOM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a low-dimensional (typically two-dimensional), discretized representation of the input space of the training samples, called a map, and is therefore a method to do dimensionality reduction. Self-organizing maps differ from other artificial neural networks as they apply competitive learning as opposed to error-correction learning (such as backpropagation with gradient descent), and in the sense that they use a neighborhood function to preserve the topological properties of the input space.

USING Instruction Step by Step

Open R Studio

First of all, let's download and activate: Kohonen and Plotly package

Now Import 2 our .data files (auto-mpg-original.data and auto-mpg.data) into project

Make sure that on Separator section, you choices Whitespace

Now import one of .R Scripts into project

(red color is our .data , yellow is our .R Scripts)

Open Script file and run this red marked section, that responsible for normalize data

And now, after normalizing data, we can call the display section and perform a kohonen function

Here each way examples

Counts Plot

Mapping Plot

SOM Neighbour Distances-Class

SOM Neighbour Distances-Cluster