By the end of this chapter, you will be able to:
- Implement logistic regression and explain how it can be used to classify data into specific groups or classes
- Use the K-nearest neighbors clustering algorithm for classification
- Use decision trees for data classification, including the ID3 algorithm
- Describe the concept of entropy within data
- Explain how decision trees such as ID3 aim to reduce entropy
- Use decision trees for data classification
This chapter introduces classification problems, classification using linear and logistic regression, K-nearest neighbors classification, and decision trees.
In the previous chapter, we began our supervised machine learning journey using ...