Data Mining with R: Learning with Case Studies, Second Edition

Luis Torgo

January 19, 2017 by Chapman and Hall/CRC
Reference - 426 Pages - 85 B/W Illustrations
ISBN 9781482234893 - CAT# K23017
Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

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Features

  • Covers the main data mining techniques through carefully selected case studies
  • Describes code and approaches that can be easily reproduced or adapted to your own problems
  • Requires no prior experience with R or ggplot
  • Includes introductions to R and MySQL basics
  • Provides a fundamental understanding of the merits, drawbacks, and analysis objectives of the data mining techniques
  • Provides code, datasets, and other supplements on the companion website: http://ltorgo.github.io/DMwR2

Summary

Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R.

The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document.

The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book.

Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining.

About the Author

Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.