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Computer Science - Image Processing | Classification and Learning Using Genetic Algorithms - Applications in Bioinformatics and Web

Classification and Learning Using Genetic Algorithms

Applications in Bioinformatics and Web Intelligence

Bandyopadhyay, Sanghamitra, Pal, Sankar Kumar

2007, XVI, 311p. 87 illus..

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  • Provides a unified framework that describes how genetic learning can be used to design pattern recognition systems

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries, and it demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks. It provides a balanced mixture of theories, algorithms and applications, and in particular results from the bioinformatics and Web intelligence domains.

This book will be useful to graduate students and researchers in computer science, electrical engineering, systems science, and information technology, both as a text and reference book. Researchers and practitioners in industry working in system design, control, pattern recognition, data mining, soft computing, bioinformatics and Web intelligence will also benefit.

Content Level » Research

Keywords » Bioinformatics - DOM - Evolutionary computation - Machine learning - Pattern recognition - Variable - Web mining - algorithms - classification - cognition - data mining - electrical engineering - genetic algorithms - intelligence - learning

Related subjects » Artificial Intelligence - Bioinformatics - Complexity - Image Processing - Signals & Communication - Software Engineering

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