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R Data Analysis Cookbook - Second Edition

You're reading from R Data Analysis Cookbook - Second Edition

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781787124479

Pages 560 pages

Edition 2nd Edition

Languages

Concepts

Authors (3):

Kuntal Ganguly

Shanthi Viswanathan

Viswa Viswanathan

View More author details

Table of Contents (14) Chapters

Preface

1. Acquire and Prepare the Ingredients - Your Data

2. What's in There - Exploratory Data Analysis

3. Where Does It Belong? Classification

4. Give Me a Number - Regression

5. Can you Simplify That? Data Reduction Techniques

6. Lessons from History - Time Series Analysis

7. How does it look? - Advanced data visualization

8. This may also interest you - Building Recommendations

9. It's All About Your Connections - Social Network Analysis

10. Put Your Best Foot Forward - Document and Present Your Analysis

11. Work Smarter, Not Harder - Efficient and Elegant R Code

12. Where in the World? Geospatial Analysis

13. Playing Nice - Connecting to Other Systems

Classifying using the support vector machine approach

The e1071 package can help you to easily apply the very powerful support vector machine (SVM) classification technique.

Getting ready

If you have not already installed the e1071 and caret packages, install them now. Download the data files for this chapter from the book's website and place the banknote-authentication.csv file in your R working directory. We will build an SVM model to predict class based on the other variables.

How to do it...

To classify using SVM, follow these steps:

Load the e1071 and caret...

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Authors (3)

Kuntal Ganguly

Kuntal Ganguly is a big data analytics engineer focused on building large-scale, data-driven systems using big data frameworks and machine learning. He has around 7 years experience of building big data and machine learning applications. Kuntal provides solutions to cloud customers in building real-time analytics systems using managed cloud services and open source Hadoop ecosystem technologies such as Spark, Kafka, Storm, Solr, and so on, along with machine learning and deep learning frameworks. Kuntal enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several large-scale distributed applications. He is a machine learning and deep learning practitioner and is very passionate about building intelligent applications.

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Shanthi Viswanathan

nan

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Viswa Viswanathan

Viswa Viswanathan is an associate professor of Computing and Decision Sciences at the Stillman School of Business in Seton Hall University. After completing his PhD in Artificial Intelligence, Viswa spent a decade in academia and then switched to a leadership position in the software industry for another decade during which he worked for Infosys, Igate, and Starbase. He embraced academia once again in 2001. Viswa has taught extensively in fields ranging from operations research, computer science, software engineering, management information systems, and enterprise systems. In addition to university teaching, Viswa has conducted training programs for industry professionals and has written several peer-reviewed research publications in journals such as Operations Research, IEEE Software, Computers and Industrial Engineering, and International Journal of Artificial Intelligence in Education. He has authored a book titled Data Analytics with R:A hands-on approach. Viswa thoroughly enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several web-based applications. Apart from his deep interest in technical fields such as data analytics, artificial intelligence, computer science, and software engineering, Viswa harbors a deep interest in education with special emphasis on the roots of learning and methods to foster deeper learning. He has done research in this area and hopes to pursue the subject further. Viswa would like to express deep gratitude to professors Amitava Bagchi and Anup Sen, who were inspirational forces during his early research career. He is also grateful to several extremely intelligent colleagues, notable among them being Rajesh Venkatesh, Dan Richner, and Sriram Bala, who significantly shaped his thinking. His aunt, Analdavalli; his sister, Sankari; and his wife, Shanthi, taught him much about hard work, and even the little he has absorbed has helped him immensely. His sons, Nitin and Siddarth, have helped with numerous insightful comments on various topics.

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