ISBN: 9783319056302
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… Plus…
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ISBN: 9783319056302
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… Plus…
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ISBN: 9783319056302
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… Plus…
ISBN: 9783319056302
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… Plus…
ISBN: 9783319056302
Scalable Pattern Recognition Algorithms - Applications in Computational Biology and Bioinformatics: ab 106.99 € eBooks > Fachthemen & Wissenschaft > Medizin Springer-Verlag GmbH eBook als… Plus…
ISBN: 9783319056302
Scalable Pattern Recognition Algorithms - Applications in Computational Biology and Bioinformatics: ab 106.99 € eBooks > Fachthemen & Wissenschaft > Medizin Springer-Verlag GmbH, Springer… Plus…
2014, ISBN: 9783319056302
Applications in Computational Biology and Bioinformatics, eBooks, eBook Download (PDF), 2014, [PU: Springer International Publishing], Springer International Publishing, 2014
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Informations détaillées sur le livre - Scalable Pattern Recognition Algorithms
EAN (ISBN-13): 9783319056302
ISBN (ISBN-10): 3319056301
Date de parution: 2014
Editeur: Springer International Publishing
Livre dans la base de données depuis 2015-01-21T16:19:44+01:00 (Paris)
Page de détail modifiée en dernier sur 2023-12-21T10:17:39+01:00 (Paris)
ISBN/EAN: 9783319056302
ISBN - Autres types d'écriture:
3-319-05630-1, 978-3-319-05630-2
Autres types d'écriture et termes associés:
Titre du livre: pattern recognition, algorithms
Données de l'éditeur
Auteur: Pradipta Maji; Sushmita Paul
Titre: Scalable Pattern Recognition Algorithms - Applications in Computational Biology and Bioinformatics
Editeur: Springer; Springer International Publishing
304 Pages
Date de parution: 2014-03-19
Cham; CH
Langue: Anglais
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XXII, 304 p. 55 illus., 10 illus. in color.
EA; E107; eBook; Nonbooks, PBS / Biologie/Sonstiges; DV-gestützte Biologie/Bioinformatik; Verstehen; Artificial Intelligence; Bioinformatics; Computational Biology; Computational Intelligence; Data Mining; Machine Learning; Medical Imaging; Pattern Recognition; Soft Computing; B; Computational and Systems Biology; Automated Pattern Recognition; Artificial Intelligence; Data Mining and Knowledge Discovery; Radiology; Computer Science; Mustererkennung; Künstliche Intelligenz; Data Mining; Wissensbasierte Systeme, Expertensysteme; Bildgebende Verfahren; BB
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 PaulRecent 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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