Discussing the article: "MQL5 Wizard Techniques you should know (Part 07): Dendrograms"
It is very good that you cover the functionality of the AlgLib library - it can be useful!
The code for visualising dendrograms is very lacking in the article.
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Check out the new article: MQL5 Wizard Techniques you should know (Part 07): Dendrograms.
Data classification for purposes of analysis and forecasting is a very diverse arena within machine learning and it features a large number of approaches and methods. This piece looks at one such approach, namely Agglomerative Hierarchical Classification.
Agglomerative Hierarchical Classification sounds like a mouthful but it’s actually quite simple. Put plainly it is a means of relating different parts of a dataset by first considering the basic individual clusters and then systematically grouping them a step at a time until the entire dataset can be viewed as a single sorted unit. The output of this process is a hierarchical diagram more commonly referred to as a Dendrogram.
This article will focus on how these constituent clusters can be used in assessing and thus forecasting price bar range but unlike in the past where we did this to help in trailing stop adjustment, we will consider it here for money management or position sizing purposes. The style to be adopted for this article will assume the reader is relatively new to the MetaTrader platform and MQL5 programming language and as such we may dwell on some topics and areas that are jejune for more experienced traders.
Author: Stephen Njuki