This
article describes techniques of operating with Kohonen maps. The
subject will be of interest to both market researchers with basic level
of programing in MQL4 and MQL5 and experienced programmers that face
difficulties with connecting Kohonen maps to their projects.
Training without a supervisor is exercised in the SOM. For training
purposes competition mechanisms are applied. When sending a pattern
network to input, the neuron with a vector that is the least different
from the input pattern wins. The following ratio applies for the winner
neuron:
where:
n — amount of neurons,
j — number of winner neuron,
d(x,w) — distance between x and w vectors.
Euclidean space is most frequently used as distance.
New article Self-organizing feature maps (Kohonen maps) - revisiting the subject has been published:
This article describes techniques of operating with Kohonen maps. The subject will be of interest to both market researchers with basic level of programing in MQL4 and MQL5 and experienced programmers that face difficulties with connecting Kohonen maps to their projects.
Training without a supervisor is exercised in the SOM. For training purposes competition mechanisms are applied. When sending a pattern network to input, the neuron with a vector that is the least different from the input pattern wins. The following ratio applies for the winner neuron:
where:
Euclidean space is most frequently used as distance.
Author: Nikolay Demko