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Like multilinear subspace methods, Multifactor Discriminant Analysis can analyze one sample in a multiple factor framework, which improves face recognition performance.
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However, Multilinear Discriminant Analysis cannot analyze multiple factor frameworks, while our proposed Multifactor Discriminant Analysis can.
In this paper, we propose an extension of LDA to multiple factor frameworks.
Our proposed method is based on an extension of LDA to multiple factor frameworks.
The extension of [6] to multiple factor frameworks cannot be simply drawn because this method is formulated only using a single factor, that is to say, subjects' identities.
Multifactor Discriminant Analysis can be thought of as an extension of LDA to multiple factor frameworks providing both multifactor analysis and discriminant analysis.
MDA can be thought of as an extension of LDA to multiple factor frameworks providing both multifactor analysis and discriminant analysis.
MPCA is a multilinear extension of Principal Component Analysis (PCA) [5] that analyzes the interaction between multiple factors utilizing a tensor framework.
This study proposes a "pyramid" framework that integrates multiple factors from different sources using the classification and regression tree (CART) algorithm, a machine learning method, to estimate soil moisture at a high spatial resolution (1 km).
Because to construct an effective instructional explanation for conceptual learning, teacher needs an "explanatory framework", which should take multiple factors into consideration including student factors, content characteristic, and learning environment etc. (Treagust and Harrison 1999, 2000; Wittwer and Renkl 2008).
As a powerful data modeling tool for pattern recognition, multilinear algebra of the higher-order tensor has been proposed as a potent mathematical framework to manipulate the multiple factors underlying the observations.
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