Discussion of article "Neural networks made easy (Part 15): Data clustering using MQL5"
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New article Neural networks made easy (Part 15): Data clustering using MQL5 has been published:
We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.
As a result of training, we obtained a graph of the dependence of the loss function on the number of clusters. It is shown below.
As you can see on the graph, the break turned out to be quite extended — in the range from 100 to 500 clusters. Totally the model analyzed more than 92 thousand system states. The form of the graph is completely identical to the one built by the Python script in the previous article. This indirectly confirms that the class we have built operates correctly.
Author: Dmitriy Gizlyk