The Data Science Workshop - Second Edition

6. How to Assess Performance

Overview

This chapter will introduce you to model evaluation, where you evaluate or assess the performance of each model that you train before you decide to put it into production. By the end of this chapter, you will be able to create an evaluation dataset. You will be equipped to assess the performance of linear regression models using mean absolute error (MAE) and mean squared error (MSE). You will also be able to evaluate the performance of logistic regression models using accuracy, precision, recall, and F1 score.

Introduction

When you assess the performance of a model, you look at certain measurements or values that tell you how well the model is performing under certain conditions, and that helps you ...