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Scalable Pattern Recognition Algorithms Applications in Computational Biology an - Maji, Pradipta und Sushmita Paul
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Maji, Pradipta und Sushmita Paul:

Scalable Pattern Recognition Algorithms Applications in Computational Biology an - libro usado

2014, ISBN: 3319056298

Unser Preis. Verlag / Jahr. von Maji, Pradipta und Sushmita Paul Maji, Pradipta und Sushmita Paul Springer International Publishing, 2014. Scalable Pattern Recognition Algorithms Applicat… Más…

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Maji, Pradipta und Sushmita Paul:

Scalable Pattern Recognition Algorithms Applications in Computational Biology an - libro usado

2014, ISBN: 3319056298

Unser Preis. Verlag / Jahr. von Maji, Pradipta und Sushmita Paul Maji, Pradipta und Sushmita Paul Springer International Publishing, 2014. Scalable Pattern Recognition Algorithms Applicat… Más…

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Scalable Pattern Recognition Algorithms : Applications in Computational Biology and Bioinformatics - Sushmita Paul
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Scalable Pattern Recognition Algorithms : Applications in Computational Biology and Bioinformatics - encuadernado, tapa blanda

2014

ISBN: 3319056298

[EAN: 9783319056296], Neubuch, [SC: 0.0], [PU: Springer International Publishing], ARTIFICIALINTELLIGENCE; COMPUTATIONALBIOLOGY; COMPUTATIONALINTELLIGENCE; DATAMINING; MACHINELEARNING; ME… Más…

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ISBN: 9783319056296

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 rec… Más…

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Scalable Pattern Recognition Algorithms Applications in Computational Biology and Bioinformatics - libro usado

2014, ISBN: 9783319056296

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Detalles del libro
Scalable Pattern Recognition Algorithms
Autor:
Título:
ISBN:

9783319056296


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.

Detalles del libro - Scalable Pattern Recognition Algorithms


EAN (ISBN-13): 9783319056296
ISBN (ISBN-10): 3319056298
Tapa dura
Tapa blanda
Año de publicación: 2014
Editorial: Springer International Publishing

Libro en la base de datos desde 2014-06-03T21:38:28+02:00 (Madrid)
Página de detalles modificada por última vez el 2023-12-21T10:17:38+01:00 (Madrid)
ISBN/EAN: 9783319056296

ISBN - escritura alterna:
3-319-05629-8, 978-3-319-05629-6
Mode alterno de escritura y términos de búsqueda relacionados:
Autor del libro: paul
Título del libro: recognition pattern, maji, bioinformatics

Datos del la editorial

Autor: Pradipta Maji; Sushmita Paul
Título: Scalable Pattern Recognition Algorithms - Applications in Computational Biology and Bioinformatics
Editorial: Springer; Springer International Publishing
304 Páginas
Año de publicación: 2014-04-04
Cham; CH
Impreso en
Idioma: Inglés
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XXII, 304 p. 55 illus., 10 illus. in color.

BB; Hardcover, Softcover / Biologie/Sonstiges; DV-gestützte Biologie/Bioinformatik; Verstehen; Artificial Intelligence; Bioinformatics; Computational Biology; Computational Intelligence; Data Mining; Machine Learning; Medical Imaging; Pattern Recognition; Soft Computing; Computational and Systems Biology; Automated Pattern Recognition; Artificial Intelligence; Data Mining and Knowledge Discovery; Radiology; Mustererkennung; Künstliche Intelligenz; Data Mining; Wissensbasierte Systeme, Expertensysteme; Bildgebende Verfahren; EA; BC

Grouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy Clustering.- Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification.- Possibilistic Biclustering for Discovering Value-Coherent Overlapping d -Biclusters.- Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images.

Part I Classification.- Part II Feature Selection.- f Part III Clustering.-

From the book reviews:

“This book provides unique insights into how various soft computing and machine learning methods can be formulated and used in building efficient pattern recognition models. … This is a great resource to students and researchers in the fields of computer science, electrical and biomedical engineering. The author has explained the complex ideas through numerous examples which make conceptualization easy. … The well-organized chapters as well as use of different notations and typescripts make it a user-friendly reference.” (Parthiv Amin, Doody’s Book Reviews, August, 2014)

is a Research Associate at the same institution.

Dr. Pradipta Maji Dr. Sushmita Paul

Recent advances in high-throughput technologies have resulted in a deluge of biological information. Yet the storage, analysis, and interpretation of such multifaceted data require effective and efficient computational tools.

This unique text/reference 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 book reviews both established and cutting-edge research, following a clear structure reflecting the major phases of a pattern recognition system: classification, feature selection, and clustering. The text provides a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics.

This important work will be of great use to graduate students and researchers in the fields of computer science, electrical and biomedical engineering. Researchers and practitioners involved in pattern recognition, machine learning, computational biology and bioinformatics, data mining, and soft computing will also find the book invaluable.

Topics and features:
Reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics Includes numerous examples and experimental results to support the theoretical concepts described Concludes each chapter with directions for future research and a comprehensive bibliography Includes supplementary material: sn.pub/extras

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