portada Data-Driven Computational Neuroscience: Machine Learning and Statistical Models (en Inglés)

Data-Driven Computational Neuroscience: Machine Learning and Statistical Models (en Inglés)

Formato

Libro Físico

Autor

Concha Bielza

Pedro Larrañaga

Editorial

Cambridge University Press

Año

2020

Idioma

Inglés

N° páginas

708

Encuadernación

Tapa Dura

Dimensiones

25.7x19.6x4.3 cm

Peso

1.50 kg.

ISBN13

9781108493703

N° edición

Categorías

Neurología y neurofisiología clínicas
Neurociencias
Reconocimiento de formas
Visión por ordenador

Data-Driven Computational Neuroscience: Machine Learning and Statistical Models (en Inglés)

Concha Bielza (Autor) · Pedro Larrañaga (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Data-Driven Computational Neuroscience: Machine Learning and Statistical Models (en Inglés)"

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.