Data-Driven Computational Neuroscience: Machine Learning and Statistical Models
Concha Bielza · Pedro Larrañaga
nov 2020 · Cambridge University Press
eBook
734
Páginas
reportLas valoraciones y las reseñas no se verifican. Más información
Información sobre este eBook
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.
Acerca del autor
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 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.
Valorar este eBook
Danos tu opinión.
Información sobre cómo leer
Smartphones y tablets
Instala la aplicación Google Play Libros para Android y iPad/iPhone. Se sincroniza automáticamente con tu cuenta y te permite leer contenido online o sin conexión estés donde estés.
Ordenadores portátiles y de escritorio
Puedes usar el navegador web del ordenador para escuchar audiolibros que hayas comprado en Google Play.
eReaders y otros dispositivos
Para leer en dispositivos de tinta electrónica, como los lectores de libros electrónicos de Kobo, es necesario descargar un archivo y transferirlo al dispositivo. Sigue las instrucciones detalladas del Centro de Ayuda para transferir archivos a lectores de libros electrónicos compatibles.
