Multilinear principal component analysis: Difference between revisions

Revision as of 19:57, 3 August 2020

Revision as of 13:53, 17 October 2020

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'''Multilinear principal component analysis''' ('''MPCA''') is a [[Multilinear algebra|multilinear]]{{dn|date=August 2020}} extension of [[principal component analysis]] (PCA). MPCA is employed in the analysis of n-way arrays, i.e. a cube or hyper-cube of numbers, also informally referred to as a "data tensor". N-way arrays may be decomposed, analyzed, or modeled by

* linear tensor models such as CANDECOMP/Parafac, or

* multilinear tensor models, such as multilinear principal component analysis (MPCA), or multilinear independent component analysis (MICA), etc.