Description
Book SynopsisData 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 in
Table of Contents
Introduction. I R AND DATA MINING. Introduction to R. Introduction to Data Mining. II CASE STUDIES. Predicting Algae Blooms. Predicting Stock Market Returns. Detecting Fraudulent Transactions. Classifying Microarray Samples
