Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Machine Learning with R

You're reading from   Machine Learning with R Expert techniques for predictive modeling to solve all your data analysis problems

Arrow left icon
Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781784393908
Length 452 pages
Edition 2nd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Brett Lantz Brett Lantz
Author Profile Icon Brett Lantz
Brett Lantz
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Introducing Machine Learning 2. Managing and Understanding Data FREE CHAPTER 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

Working with online data and services

With the growing amount of data available from web-based sources, it is increasingly important for machine learning projects to be able to access and interact with online services. R is able to read data from online sources natively, with some caveats. Firstly, by default, R cannot access secure websites (those using the https:// rather than the http:// protocol). Secondly, it is important to note that most web pages do not provide data in a form that R can understand. The data would need to be parsed, or broken apart and rebuilt into a structured form, before it can be useful. We'll discuss the workarounds shortly.

However, if neither of these caveats applies (that is, if data are already online on a nonsecure website and in a tabular form, like CSV, that R can understand natively), then R's read.csv() and read.table() functions will be able to access data from the Web just as if it were on your local machine. Simply supply the full URL for...

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 €18.99/month. Cancel anytime