Higher Education


Data Mining Techniques and Applications : An Introduction

Author(s): Hongbo Du

ISBN: 9788131519554

1st Edition

Copyright: 2013

India Release: 2013


Binding: Paperback

Pages: 334

Trim Size: 241 x 181 mm

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This concise and approachable introduction to data mining selects a mixture of data mining techniques originating from statistics, machine learning and databases, and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way, but also hands on, practical instruction on data mining techniques, that readers can put into practice as they go along using Weka toolkit.

  • Practical, hands-on instruction in data mining techniques using Weka
  • Provides an easy-to-follow coverage of data mining algorithms via use of pseudo code and abstract data structures together with illustrative examples
  • Real-life case study and examples demonstrating the practical applications of data mining techniques.

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.

Hongbo Du

Hongbo Du is a lecturer in the Applied Computing Department, University of Buckingham, and specializes in database systems and data mining.