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Books > Social sciences > Psychology > Cognition & cognitive psychology
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Data-Driven Computational Neuroscience - Machine Learning and Statistical Models (Hardcover)
Loot Price: R2,265
Discovery Miles 22 650
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Data-Driven Computational Neuroscience - Machine Learning and Statistical Models (Hardcover)
Expected to ship within 12 - 17 working days
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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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