Design and Implementation of Data Mining Tools
Autor Bhavani Thuraisingham, Latifur Khan, Mamoun Awad, Lei Wangen Limba Engleză Paperback – 19 sep 2019
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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Specificații
ISBN-13: 9780367385552
ISBN-10: 0367385554
Pagini: 272
Dimensiuni: 156 x 234 x 18 mm
Greutate: 0.51 kg
Ediția:1
Editura: CRC Press
Colecția Auerbach Publications
ISBN-10: 0367385554
Pagini: 272
Dimensiuni: 156 x 234 x 18 mm
Greutate: 0.51 kg
Ediția:1
Editura: CRC Press
Colecția Auerbach Publications
Public țintă
Academic and Professional Practice & DevelopmentCuprins
Data Mining Techniques and Applications. Data Mining Tool for Intrusion Detection. Data Mining Tool for Web Page Surfing Prediction. Data Mining Tool for Image Classification. Appendix. Index.
Notă biografică
Thuraisingham, Bhavani; Khan, Latifur; Awad, Mamoun; Wang, Lei
Descriere
Based on the authors’ own research work, this book explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Focusing on three applications of data mining, the book takes a practical approach to the subject. A hands-on guide, it 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.