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
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Example – predicting medical expenses using linear regression

In order for a health insurance company to make money, it needs to collect more in yearly premiums than it spends on medical care to its beneficiaries. Consequently, insurers invest a great deal of time and money to develop models that accurately forecast medical expenses for the insured population.

Medical expenses are difficult to estimate because the costliest conditions are rare and seemingly random. Still, some conditions are more prevalent for certain segments of the population. For instance, lung cancer is more likely among smokers than non-smokers, and heart disease may be more likely among the obese.

The goal of this analysis is to use patient data to forecast the average medical care expenses for such population segments. These estimates could be used to create actuarial tables that set the price of yearly premiums higher or lower according to the expected treatment costs.

Step 1 – collecting data

For this analysis, we will...