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

By: (Author) Luis Torgo

Extended Catalogue

Ksh 15,300.00

Format: Hardback or Cased Book

ISBN-10: 1482234890

ISBN-13: 9781482234893

Edition Number: 2

Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Publisher: Taylor & Francis Inc

Imprint: Chapman & Hall/CRC

Country of Manufacture: CA

Country of Publication: GB

Publication Date: Jan 19th, 2017

Print length: 426 Pages

Weight: 1,046 grams

Dimensions (height x width x thickness): 18.80 x 26.20 x 2.20 cms

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  • Description

  • Reviews

If you want to learn how to analyze your data with R, this is your book. A broad range of real-world case studies highlights the breadth and depth of the R software. This expanded second edition delves deeper into topical explanations and updates and expands all case studies. Assuming no prior knowledge of R or data mining/statistical techniques, the book covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools.

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.


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