Kohonen Self-Organizing Maps.*;

 

Code Example Set 1

A Kohonen Self-Organizing Network with 4 Inputs and 2-Node Linear Array of Cluster Units.

The results will vary slightly with different combinations of learning rate, decay rate, and alpha value.


Example Results

After 101 iterations, this code would produce the following results:

Iterations: 101
Clusters for training input:
Vector (1, 1, 0, 0, ) fits into category 1
Vector (0, 0, 0, 1, ) fits into category 0
Vector (1, 0, 0, 0, ) fits into category 1
Vector (0, 0, 1, 1, ) fits into category 0
Weights for Node 0 connections:
.000, .000, .508, 1.000,
Weights for Node 1 connections:
1.000, .492, .000, .000,
Categorized test input:
Vector (1, 0, 0, 1, ) fits into category 1
Vector (0, 1, 1, 0, ) fits into category 0
Vector (1, 0, 1, 0, ) fits into category 1
Vector (0, 1, 0, 1, ) fits into category 0
		
public void footer() {
About | Contact | Privacy Policy | Terms of Service | Site Map
Copyright© 2009-2012 John McCullock. All Rights Reserved.
}