Regression

Another powerful yet easy-to-understand algorithm is regression. Regression is another supervised machine learning algorithm. Regression algorithms return a real value as opposed to a binary algorithm or ones that return from a set of specific values. You can think of regression algorithms as an algebra equation solver where there are a number of known values and the goal is to predict the one unknown value. Some examples of problems best suited to regression algorithms are predicting attrition, weather forecasting, stock market predictions, and house pricing, to name a few. 

In addition, there is a subset of regression algorithms called logistic regression models. Whereas a traditional linear regression algorithm, as described earlier, returns the predicted value, a logistic regression model will return the probability of the outcome occurring.

ML.NET provides several regression model algorithms, which we will cover in Chapter 3, Regression Model.