Discussion of article "Data Science and Machine Learning (Part 07): Polynomial Regression"

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New article Data Science and Machine Learning (Part 07): Polynomial Regression has been published:

Unlike linear regression, polynomial regression is a flexible model aimed to perform better at tasks the linear regression model could not handle, Let's find out how to make polynomial models in MQL5 and make something positive out of it.

We are not through with regression models, we are back in it for a second. As I said in the first article of this series the basic linear regression serves as a foundation for many machine learning models and today we are going to discuss something a little bit different from linear regression known as Polynomial regression.

Machine Learning has changed our world a lot in many ways, we have different methods to learn the training data for classification and regression problems, such as linear regression, logistic regression, support vector machine, polynomial regression, and many other techniques, Some parametric methods like polynomial regression and support vector machines stand out as being versatile.

They create simple boundaries for simple problems and nonlinear boundaries for complex problems

Author: Omega J Msigwa