Note
Learning Objectives
By the end of this chapter, you will be able to:
Explain supervised learning and machine learning workflow
Use and explore the Beijing PM2.5 dataset
Explain the difference between continuous and categorical dependent variables
Implement the basic regression and classification algorithms in R
Identify the key differences between supervised learning and other types of machine learning
Work with the evaluation metrics of supervised learning algorithms
Perform model diagnostics for avoiding biased coefficient estimates and large standard errors