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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.

Product type Paperback

Published in Oct 2013

Publisher Packt

ISBN-13 9781782162148

Length 396 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Brett Lantz

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Table of Contents (19) Chapters

Machine Learning with R

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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

Summary

In this chapter, we learned about the basics of managing data in R. We started by taking an in-depth look at the structures used for storing various types of data. The foundational R data structure is the vector, which is extended and combined into more complex data types such as lists and data frames. The data frame is an R data structure that corresponds to the notion of a dataset, having both features and examples.

We also learned about how to get data into R from a variety of sources. R provides functions for reading from and saving to CSV files; SQL databases can be queried with the RODBC package.

Finally, we applied these skills while exploring a real-world dataset containing data on used car prices. We examined numeric variables using common summary statistics of center and spread, and visualized relationships between prices and odometer readings with a scatterplot. We examined nominal variables using tables. In examining the used car data, we followed an exploratory process...

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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.

Table of Contents (19) Chapters

Summary

Authors (1)

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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.

Table of Contents (19) Chapters

Summary

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