Design and Implementation of Data Mining Tools
Language: English
Published by Taylor & Francis Ltd Jun 2009, 2009
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 178.96
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Add to basketItem description from seller
Neuware - Design and Implementation of Data Mining Tools presents a step by step approach that demonstrates how data mining tools are developed. This book discusses intrusion detection for security application, web page prediction for e-commerce application, and image classification for multimedia application. It provides experimental performance results, examines unique contributions, and addresses limitations for each system. Additional coverage includes supporting technologies such as artificial neural networks, future directions for data mining applications, and data management systems. This text is a practical guide for the industry.
Seller Inventory # 9781420045901
- Title
- Design and Implementation of Data Mining Tools
- Author
- Bhavani Thuraisingham
- Publisher
- Taylor & Francis Ltd Jun 2009
- Publication year
- 2009
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1420045903
- ISBN 13
- 9781420045901
- Item weight
- 600 grams
- Dimensions
- 234x156x0 mm
Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors’ own research work, the book takes a practical approach to the subject.
The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification.
Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.
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