WISDoM: Characterizing Neurological Time Series With the Wishart Distribution

WISDoM: Characterizing Neurological Time Series With the Wishart Distribution

WISDoM (Wishart Distributed Matrices) is a framework for the quantification of deviation of symmetric positive-definite matrices associated with experimental samples, such as covariance or correlation matrices, from expected ones governed by the Wishart distribution. WISDoM can be applied to tasks o...

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Bibliographic Details
Main Authors: Carlo Mengucci, Daniel Remondini, Gastone Castellani, Enrico Giampieri
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Neuroinformatics
Subjects:
supervised learning
time series
null model
feature selection
classification
Wishart distribution
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2020.611762/full

Internet

https://www.frontiersin.org/articles/10.3389/fninf.2020.611762/full

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