Say you have a company or want to invest in a company, and you want to predict how much it will grow in the coming months or years. How to do that?
Here we will show how this problem can be modeled in a very simple way using symbolic regression.Read More
Symbolic regression is a method that discovers mathematical formulas from data without assumptions on what those formulas should look like. Given a set of input variables x1, x2, x3, etc, and a target variable y, it will use trial and error find f such that y = f(x1, x2, x3, …).Read More
When it comes to AI, neural networks are the first method that comes to mind. Despite their impressive performance on a number of applications, we want to argue that they are not necessarily a good general-purpose machine learning method.Read More
In order to find an equation from a list of values, a special technique called symbolic regression must be used. The idea is to search over the space of all possible mathematical formulas for the ones with the greatest accuracy, while trying to keep those formulas as simple as possible.Read More
Regression models are perhaps the most important class of machine learning models. In this tutorial, we will show how to easily generate a regression model from data values.Read More