Data Mining with Rattle and R. The art of excavating data for knowledge discovery.

*(English)*Zbl 1267.68008
Use R!. New York, NY: Springer (ISBN 978-1-4419-9889-7/pbk; 978-1-4419-9890-3/ebook). xx, 374 p. (2011).

A wide range of techniques and algorithms are used in data mining. This book introduces the basic concepts and algorithms of data mining and uses the free and open source software Rattle which is built on top of the R statistical software package. R, which is supported by a worldwide network of statisticians, implements all of the key algorithms for data mining. A key feature of this book, which differentiates it from many other books on data mining, is the focus on the hands-on end-to-end process for data mining.

This book not only covers data understanding, data preparation, model building, model evaluation, data refinement, and practical deployment, but also provides a very practical resource with actual examples using Rattle. This book guides the reader through the various options Rattle provides and serves to guide the new data miner through the use of Rattle. Many excursions into using R itself are presented, with the aim of encouraging readers to use R directly as a scripting language. This book provides excursions into the command line, giving numerous examples of direct interaction with R.

This book not only covers data understanding, data preparation, model building, model evaluation, data refinement, and practical deployment, but also provides a very practical resource with actual examples using Rattle. This book guides the reader through the various options Rattle provides and serves to guide the new data miner through the use of Rattle. Many excursions into using R itself are presented, with the aim of encouraging readers to use R directly as a scripting language. This book provides excursions into the command line, giving numerous examples of direct interaction with R.

Reviewer: Sang Ho Lee (Seoul)

##### MSC:

68-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science |

68P01 | General topics in the theory of data |

68P99 | Theory of data |