Chapter 4

Classification

Learning Objectives

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.

Introduction

In the previous chapter, we began our supervised machine learning journey using ...

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