Book Image

Machine Learning with R - Third Edition

By : Brett Lantz
Book Image

Machine Learning with R - Third Edition

By: Brett Lantz

Overview of this book

Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.
Table of Contents (18 chapters)
Machine Learning with R - Third Edition
Other Books You May Enjoy
Leave a review - let other readers know what you think

Chapter 10. Evaluating Model Performance

When only the wealthy could afford education, tests and exams did not evaluate the students. Instead, tests judged teachers for parents who wanted to know whether their children learned enough to justify the instructors' wages. Obviously, this is different today. Now, such evaluations are used to distinguish between high-achieving and low-achieving students, filtering them into careers and other opportunities.

Given the significance of this process, a great deal of effort is invested in developing accurate student assessments. Fair assessments have a large number of questions that cover a wide breadth of topics and reward true knowledge over lucky guesses. A good assessment also requires students to think about problems they have never faced before. Correct responses therefore reflect an ability to generalize knowledge more broadly.

The process of evaluating machine learning algorithms is very similar to the process of evaluating students. Since algorithms...