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Principles of Data Mining

  • Max Bramer

About this book

Introduction

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.

Keywords

Algorithms Artificial Intelligence Data Mining Databases Knowledge Discovery algorithm classification performance

Authors and affiliations

  • Max Bramer
    • 1
  1. 1.Digital Professor of Information TechnologyUniversity of PortsmouthUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-84628-766-4
  • Copyright Information Springer-Verlag London Limited 2007
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-84628-765-7
  • Online ISBN 978-1-84628-766-4
  • Buy this book on publisher's site
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