Data-Driven Computational Neuroscience : Machine Learning and Statistical Models
Language: English
Published by Cambridge University Press Jan 2021, 2021
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 139.77
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Add to basketItem description from seller
Neuware - Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with point processes (complete spatial randomness and cluster, regular and Gibbs processes). Cellular, structural, functional, medical and behavioral neuroscience levels are considered.…
Seller Inventory # 9781108493703
- Title
- Data-Driven Computational Neuroscience : Machine Learning and Statistical Models
- Author
- Concha Bielza
- Publisher
- Cambridge University Press Jan 2021
- Publication year
- 2021
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 110849370X
- ISBN 13
- 9781108493703
- Item weight
- 1,497 grams
- Dimensions
- 257x196x43 mm
"Synopsis" may belong to another edition of this title.
About the Author
Pedro Larrañaga is a professor in the Department of Artificial Intelligence at Universidad Politécnica de Madrid. He has published more than 150 journal papers and coauthored the book Industrial Applications of Machine Learning (2019). He is fellow of the European Association for Artificial Intelligence and of Academia Europaea.
"About the title" may belong to another edition of this title.
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