Scalable Pattern Recognition Algorithms
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This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
![Scalable Pattern Recognition Algorithms Scalable Pattern Recognition Algorithms](https://cos.richshop.de/servlet/images/9783319056302.jpg?w=300)
- Autor: Pradipta Maji / Sushmita Paul
- Format: PDF
- DRM: social-drm (ohne Kopierschutz)
- Erscheinungsdatum: 19.03.2014
- Herausgeber: SPRINGER