Multilinear principal component analysis
id:
multilinear-principal-component-analysis-298-12892892
title:
Multilinear principal component analysis
text:
Multilinear principal component analysis (MPCA) is a 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 introduc
brand slug:
wiki
category slug:
encyclopedia
description:
Multilinear extension of principal component analysis
original url:
https://en.wikipedia.org/wiki/Multilinear_principal_component_analysis
date created:
date modified:
2024-03-10T02:13:22Z
main entity:
{"identifier":"Q6934740","url":"https://www.wikidata.org/entity/Q6934740"}
image:
fields total:
13
integrity:
14