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Machine Learning with R

You're reading from   Machine Learning with R R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required ‚Äì this book will take you methodically through every stage of applying machine learning.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781782162148
Length 396 pages
Edition 1st Edition
Languages
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Author (1):
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Brett Lantz Brett Lantz
Author Profile Icon Brett Lantz
Brett Lantz
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Table of Contents (19) Chapters Close

Machine Learning with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Introducing Machine Learning FREE CHAPTER 2. Managing and Understanding Data 3. Lazy Learning – Classification Using Nearest Neighbors 4. Probabilistic Learning – Classification Using Naive Bayes 5. Divide and Conquer – Classification Using Decision Trees and Rules 6. Forecasting Numeric Data – Regression Methods 7. Black Box Methods – Neural Networks and Support Vector Machines 8. Finding Patterns – Market Basket Analysis Using Association Rules 9. Finding Groups of Data – Clustering with k-means 10. Evaluating Model Performance 11. Improving Model Performance 12. Specialized Machine Learning Topics Index

Chapter 4. Probabilistic Learning – Classification Using Naive Bayes

When a meteorologist provides a weather forecast, precipitation is typically predicted using terms such as "70 percent chance of rain." These forecasts are known as probability of precipitation reports. Have you ever considered how they are calculated? It is a puzzling question, because in reality, it will either rain or it will not.

These estimates are based on probabilistic methods, or methods concerned with describing uncertainty. They use data on past events to extrapolate future events. In the case of weather, the chance of rain describes the proportion of prior days with similar measurable atmospheric conditions in which precipitation occurred. A 70 percent chance of rain therefore implies that in 7 out of 10 past cases with similar weather patterns, precipitation occurred somewhere in the area.

This chapter covers a machine learning algorithm called naive Bayes, which also uses principles of probability for classification...

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