The main goal of this book is to introduce the reader to the use of R as a
tool for data mining. R is a freely downloadable1 language and environment
for statistical computing and graphics. Its capabilities and the large set of
available add-on packages make this tool an excellent alternative to many
existing (and expensive!) data mining tools.
One of the key issues in data mining is size. A typical data mining problem
involves a large database from which one seeks to extract useful knowledge.
In this book we will use MySQL as the core database management system.
MySQL is also freely available2 for several computer platforms. This means
that one is able to perform \serious" data mining without having to pay any
money at all. Moreover, we hope to show that this comes with no compromise
of the quality of the obtained solutions. Expensive tools do not necessarily
mean better tools! R together with MySQL form a pair very hard to beat as
long as one is willing to spend some time learning how to use them. We think
that it is worthwhile, and we hope that at the end of reading this book you
are convinced as well.
The goal of this book is not to describe all facets of data mining processes.
Many books exist that cover this scientic area. Instead we propose to introduce
the reader to the power of R and data mining by means of several case
studies. Obviously, these case studies do not represent all possible data mining
problems that one can face in the real world. Moreover, the solutions we
describe cannot be taken as complete solutions. Our goal is more to introduce
the reader to the world of data mining using R through practical examples.
As such, our analysis of the case studies has the goal of showing examples of
knowledge extraction using R, instead of presenting complete reports of data
mining case studies.