Multilinear principal component analysis: Difference between revisions

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{{short description|Multilinear extension of principal component analysis}}

'''Multilinear principal component analysis''' ('''MPCA''') is a [[Multilinear algebra|multilinear]] extension of [[principal component analysis]] (PCA) that is used to analyze M-way arrays, also informally referred to as "data tensors". M-way arrays may be modeled by linear tensor models, such as CANDECOMP/Parafac, or by multilinear tensor models, such as multilinear principal component analysis (MPCA) or multilinear independent component analysis (MICA).

The origin of MPCA can be traced back to the [[Tensor rank decomposition|tensor rank decomposition]] introduced by [[Frank Lauren Hitchcock]] in 1927;<ref>{{Cite journal

| author = F. L. Hitchcock

| author-link = F. L. Hitchcock