As mentioned earlier, the application we will be creating is an employee attrition predictor. Given a set of attributes tied to an employee, we can predict how long they will remain at their current job. The attributes included in this example aren't a definitive list of attributes, nor should be used as-is in a production environment; however, we can use this as a starting point for predicting a singular numeric output based on several attributes.
As with Chapter 1, Getting Started with Machine Learning and ML.NET, the completed project code, sample dataset, and project files can be downloaded here: https://github.com/PacktPublishing/Hands-On-Machine-Learning-With-ML.NET/tree/master/chapter03_linear_regression.
Diving into the trainer
As previously mentioned, for this linear regression application, we will be using the SDCA trainer. SDCA stands for Stochastic Dual Coordinate Ascent and if you may recall, we used the logistic regression...
