Book Image

Mastering Predictive Analytics with R

By : Rui Miguel Forte, Rui Miguel Forte
Book Image

Mastering Predictive Analytics with R

By: Rui Miguel Forte, Rui Miguel Forte

Overview of this book

Table of Contents (19 chapters)
Mastering Predictive Analytics with R
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Loading and preprocessing the data


Our first goal in building our recommender systems is to load the data in R, preprocess it, and convert it into a rating matrix. More precisely, in each case, we will be creating a realRatingMatrix object, which is the specific data structure that the recommenderlab package uses to store numerical ratings. We will start with the jester data set. If we download and unzip the archive from the website, we'll see that the file jesterfinal151cols.csv contains the ratings. More specifically, each row in this file corresponds to the ratings made by a particular user, and each column corresponds to a particular joke.

The columns are comma-separated and there is no header row. In fact, the format is almost exactly already a rating matrix were it not for the fact that the first column is a special column and contains the total number of ratings made by a particular user. We will load these data into a data table using the function fread(), which is a fast implementation...