Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Predictive Analytics with R

You're reading from   Mastering Predictive Analytics with R Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts

Arrow left icon
Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783982806
Length 414 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Toc

Table of Contents (13) Chapters Close

Preface 1. Gearing Up for Predictive Modeling 2. Linear Regression FREE CHAPTER 3. Logistic Regression 4. Neural Networks 5. Support Vector Machines 6. Tree-based Methods 7. Ensemble Methods 8. Probabilistic Graphical Models 9. Time Series Analysis 10. Topic Modeling 11. Recommendation Systems Index

Predicting chemical biodegration


In this section, we are going to use R's e1071 package to try out the models we've discussed on a real-world data set. As our first example, we have chosen the QSAR biodegration data set, which can be found at https://archive.ics.uci.edu/ml/datasets/QSAR+biodegradation#. This is a data set containing 41 numerical variables that describe the molecular composition and properties of 1055 chemicals. The modeling task is to predict whether a particular chemical will be biodegradable based on these properties. Example properties are the percentages of carbon, nitrogen, and oxygen atoms as well as the number of heavy atoms in the molecule. These features are highly specialized and sufficiently numerous, so a full listing won't be given here. The complete list and further details of the quantities involved can be found on the website. For now, we've downloaded the data into a bdf data frame:

> bdf <- read.table("biodeg.csv", sep = ";", quote = "\"")
> head...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image