Data-Driven Computational Neuroscience: Machine Learning and Statistical Models - Hardcover

Bielza, Concha; Larraņaga, Pedro

 
9781108493703: Data-Driven Computational Neuroscience: Machine Learning and Statistical Models
Hardcover
ISBN 10: 110849370X ISBN 13: 9781108493703
Publisher: Cambridge University Press, 2020

Synopsis

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.

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About the Authors

Concha Bielza is a professor in the Department of Artificial Intelligence at Universidad Politécnica de Madrid. She has published more than 120 journal papers and coauthored the book Industrial Applications of Machine Learning (2019). She was awarded the 2014 UPM Research Prize.

Pedro Larraņaga 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 this title" may belong to another edition of this title.

Publisher
Cambridge University Press
Publication date
2020
Language
English
ISBN 10 
110849370X
ISBN 13 
9781108493703
Binding
Hardcover
Edition number
1
Number of pages
708