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Mastering Machine Learning with R

You're reading from   Mastering Machine Learning with R Master machine learning techniques with R to deliver insights for complex projects

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783984527
Length 400 pages
Edition 1st Edition
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Author (1):
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Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
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Table of Contents (15) Chapters Close

Preface 1. A Process for Success FREE CHAPTER 2. Linear Regression – The Blocking and Tackling of Machine Learning 3. Logistic Regression and Discriminant Analysis 4. Advanced Feature Selection in Linear Models 5. More Classification Techniques – K-Nearest Neighbors and Support Vector Machines 6. Classification and Regression Trees 7. Neural Networks 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis and Recommendation Engines 11. Time Series and Causality 12. Text Mining A. R Fundamentals Index

Installing and loading the R packages

We discussed earlier how to install an R package using the install() function. To use an installed package, you also need to load it to be able to use it. Let's go through this again, first with the installation in RStudio and then loading the package. Look for and click the Packages tab. You should see something similar to this:

Installing and loading the R packages

Now, let's install the R package, xgboost. Click on the Install icon and type the package name in the Packages section of the popup:

Installing and loading the R packages

Click the Install button. Once the package has been fully installed, the command prompt will return. To load the package in order to be able to use it, only the library() function is required:

> library(xgboost)

With this, you are now able to use the functions built in the package.

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