With our development environment configured and our first ML.NET application completed, it is now time to dive into regression models. In this chapter, we will dive into the math behind regression models, as well as the various applications of regression models. We will also build two additional ML.NET applications, one utilizing a linear regression model and the other a logistic regression model. The linear regression application will predict employee attrition based on various employee attributes. The logistic regression application will perform basic static file analysis on a file to determine whether it is malicious or benign. Finally, we will explore how to evaluate a regression model with the properties ML.NET exposes in regression models.
In this chapter, we will cover the following topics:
- Breaking down various regression models
- Creating the linear regression...
