Discussing the article: "MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression"
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Check out the new article: MQL5 Wizard Techniques you should know (Part 20): Symbolic Regression.
Symbolic Regression is a form of regression that starts with minimal to no assumptions on what the underlying model that maps the sets of data under study would look like. Even though it can be implemented by Bayesian Methods or Neural Networks, we look at how an implementation with Genetic Algorithms can help customize an expert signal class usable in the MQL5 Wizard.
We continue these series where we look at algorithms that can be quickly coded, tested, and perhaps even deployed all thanks to the MQL5 wizard that not only has a library of standard trading functions and classes that accompany a coded Expert Advisor, but also has alternative trade signals and methods which can be used in parallel with any custom class implementation.
Symbolic regression is a variant of regression analysis that starts with more of a ‘blank slate’ than its traditional cousin, classical regression. The best way to illustrate this would be if we consider the typical regression problem that is seeking the slope and y intercept to a line that best fits a set of data points.
Author: Stephen Njuki