Data Mining, the automatic extraction of
implicit and potentially useful information from data, is increasingly
used in commercial, scientific and other application areas.
This book explains and explores the principal techniques
of Data Mining: for classification, generation of association rules and
clustering. It is written for readers without a strong background in mathematics
or statistics and focuses on detailed examples & explanations of the
algorithms given. It can be used as a textbook to support courses at undergraduate
or postgraduate levels in a wide range of subjects including Computer
Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics
and Forensic Science.
As an aid to self study, this book aims to help the general
reader develop the necessary understanding to use commercial data mining
packages discriminatingly, as well as enabling the advanced reader or
academic researcher to understand or contribute to future technical advances
in the field. Each chapter has practical exercises to enable readers to
check their progress. A full glossary of technical terms used is included.