Rigorous optimisation of multilinear discriminant analysis with Tucker and PARAFAC structures

Rigorous optimisation of multilinear discriminant analysis with Tucker and PARAFAC structures

Abstract Background We propose rigorously optimised supervised feature extraction methods for multilinear data based on Multilinear Discriminant Analysis (MDA) and demonstrate their usage on Electroencephalography (EEG) and simulated data. While existing MDA methods use heuristic optimisation proced...

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Bibliographic Details
Main Authors: Laura Frølich, Tobias Søren Andersen, Morten Mørup
Format: Article
Language:English
Published: BMC 2018-05-01
Series:BMC Bioinformatics
Subjects:
Multilinear discriminant analysis
Electroencephalography
EEG
Tensor
Classification
Stiefel manifold
Online Access:http://link.springer.com/article/10.1186/s12859-018-2188-0

Internet

http://link.springer.com/article/10.1186/s12859-018-2188-0

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