So far, we have only learned about neural networks for classification problems. But in this chapter, we will learn about one of the most important topics surrounding behavioral cloning: neural network for regression. The main aim of classification problems is to group the classes of objects into categories and predict the category of the class later. For example, cat and dog can be two different classes.
Now, we will look into a regression type example, where we will use linear regression to predict continuous values based on the relationship between the independent variable (X) and the dependent variable (y). In general, linear regression helps us predict values on a continuous spectrum, rather than on discrete classes.
The following is a linear regression plot:
Linear regression is the simplest form of regression. The goal is to find the line parameterized by the set of slope and y-intercept...
