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Data Mining Techniques and Applications
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Table of Contents

1. Introduction
2. Principles of Data Mining
3. Data, Data Pre-processing and Data Exploration
4. Basic Techniques for Cluster Detection
5. Advanced Techniques for Cluster Detection
6. Decision Tree Induction Techniques for Classification
7. Other Techniques for Classification
8. Techniques for Boolean Association Rule Discovery
9. Techniques for Other Types of Association Rules
10. Data Mining in Practice

About the Author

Hongbo Du is a lecturer in the Applied Computing Department, University of Buckingham, and specializes in database systems and data mining. He has been teaching data mining to undergraduate students and taught master students since 1997. He also designed and taught a similar course at City University London between 1998 and 2004, and more recently at Sarajevo School of Science and Technology. Author of a number of publications in the field, he has been involved with commercial data mining projects. He is also a visiting senior lecturer at Sarajevo School of Science and Technology.

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1. Introduction 2. Principles of Data Mining 3. Data, Data Pre-processing and Data Exploration 4. Basic Techniques for Cluster Detection 5. Advanced Techniques for Cluster Detection 6. Decision Tree Induction Techniques for Classification 7. Other Techniques for Classification 8. Techniques for Boolean Association Rule Discovery 9. Techniques for Other Types of Association Rules 10. Data Mining in Practice

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