Data Science Projects with Python

Chapter 3:

Details of Logistic Regression and Feature Exploration

Learning Objectives

By the end of this chapter, you will be able to:

• Write list comprehensions in Python
• Describe the workings of logistic regression
• Formulate the sigmoid and logit versions of logistic regression
• Utilize univariate feature selection to find important features
• Customize plots with the Matplotlib API
• Characterize the linear decision boundary of a logistic regression

This chapter presents the basics of logistic regression along with various other methods for examining the relationship between features and a response variable.

Introduction

In the previous chapter, we concluded our examination of the response variable, and developed a few example machine ...