Table of contents

  1. Front Matter
    Pages I-XIV
  2. Max Bramer
    Pages 1-8
  3. Max Bramer
    Pages 9-19
  4. Max Bramer
    Pages 93-119
  5. Max Bramer
    Pages 121-136
  6. Max Bramer
    Pages 137-156
  7. Max Bramer
    Pages 189-208
  8. Max Bramer
    Pages 209-220
  9. Max Bramer
    Pages 221-236
  10. Max Bramer
    Pages 237-251
  11. Max Bramer
    Pages 253-269
  12. Max Bramer
    Pages 311-328
  13. Max Bramer
    Pages 329-343
  14. Back Matter
    Pages 345-440

About this book


Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail.

This second edition has been expanded to include additional chapters on using frequent pattern trees for Association Rule Mining, comparing classifiers, ensemble classification and dealing with very large volumes of data.

Principles of Data Mining aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.

Suitable 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.


Associate Rule Mining Attribute Selection Classification Classifiers Clustering Data Mining Datasets Decision Trees Entropy

Authors and affiliations

  • Max Bramer
    • 1
  1. 1.School of ComputingUniversity of PortsmouthPortsmouthUnited Kingdom

Bibliographic information

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