The purpose of this appendix was to allow the R novice to learn the basics of the programming language and prepare them for the code in the book. This consisted of learning how to install R and RStudio and creating objects, vectors, and matrices. Then, we explored some of the mathematical and statistical functions. Finally, we covered how to install and load a package in R using RStudio. Throughout the appendix, the plot syntax for the base and examples are included. While this appendix will not make you an expert in R, it will get you up to speed to follow along with the examples in the book.
Mastering Machine Learning with R
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Mastering Machine Learning with R
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Overview of this book
Table of Contents (20 chapters)
Mastering Machine Learning with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
A Process for Success
Linear Regression – The Blocking and Tackling of Machine Learning
Logistic Regression and Discriminant Analysis
Advanced Feature Selection in Linear Models
More Classification Techniques – K-Nearest Neighbors and Support Vector Machines
Classification and Regression Trees
Neural Networks
Cluster Analysis
Principal Components Analysis
Market Basket Analysis and Recommendation Engines
Time Series and Causality
Text Mining
R Fundamentals
Index
Customer Reviews