Scalable Pattern Recognition Algorithms - Applications in Computational Biology and Bioinformatics (Paperback, Softcover reprint of the original 1st ed. 2014)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	August 2016
First published:	2014
Authors:	Pradipta Maji • Sushmita Paul
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	304
Edition:	Softcover reprint of the original 1st ed. 2014
ISBN-13:	978-3-319-37965-4
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Medicine > Other branches of medicine > Medical imaging > Radiology Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-37965-8
Barcode:	9783319379654

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