SAS Data Mining Tools Drive Growing Segment of Business ...
Design and Implementation of Efficient Search Methodology for Content-Based Retrieval in ELearning Environment
DESIGN AND IMPLEMENTATION OF NETWORK SECURITY USING GENETIC ALGORITHM
DESIGN AND IMPLEMENTATION OF AN ANCRCHITECTURE OF EMBEDDED WEB SERVER FOR WIRELESS SENSOR NETWORK
The Design and Implementation of Educational Software: for energy saving
Design and Implementation of Administrator Session Monitoring
DESIGN AND IMPLEMENTATION OF AUTONOMOUS MANEUVERING ROBOTIC VEHICLE USING GLOBAL POSITIONING SYSTEM FOR JAMMING THE COMMUNICATION DURING WARFARE
Design and Implementation of Proportional Integral Observer based Linear Model Predictive Controller
Design and Implementation of Discrete Augmented Ziegler-Nichols PID Controller
The Design and Implementation of Educational Software
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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