SOM classification on variables

Introduction

I use the SOM toolbox to extract my classification . It is a kohonen approach on Self Map Organisation.

It is a puissant tool to classify the metric data. Near a neural network method, the algorithm construct at each step a map reorganized to fit the best grouping on the selected map element (columns and rows).

This approach reveal than races are not an essential reference to classify the variables.

A Map of 6x6

This map is really well balanced. 

On top left, we concentrate median people.

On top right, we concentrate nice people (white, speaking english ,...)

On bottom left , we concentrate immigrant and population density

On bottom right, we concentrate immigrant and social.

On bottom middle our value to predict the violent crime.

It is a good map. Each variable found a perfect place. 

A Map of 2x2

I have reduced the map to a 2x2 to obtain more grouped variables. It s not innocent . It s because I need some opposable variables to our predict value for filter data in prediction research. You will see this feature in the next message.
Now on this map:
On the top left we have immigrant , illegitime,density, urban,poverty and our targeted variable to predict.
On the top right we have immigrant , manual employment,social,education.
On the bottom left  we have medium family.
On the bottom right  we found the ideal family speaking english with 2 children, living on the same area. The opposite of the violent crime