Adaptive dimensionality reduction for neural network-based online principal component analysis

“Principal Component Analysis” (PCA) is an established linear technique for dimensionality reduction. It performs an orthonormal transformation to replace possibly correlated variables with a smaller set of linearly independent variables, the so-called principal components, which capture a large por...

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Bibliographic Details
Published in:	PloS one Vol. 16; no. 3; p. e0248896
Main Authors:	Migenda, Nico, Möller, Ralf, Schenck, Wolfram
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 30.03.2021 Public Library of Science (PLoS)
Subjects:	Algorithms Biology and Life Sciences Computer and Information Sciences Computer applications Data points Datasets Distance learning Eigenvalues Electronic data processing Machine learning Methods Neural networks Physical Sciences Principal components analysis Research and Analysis Methods Germany
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
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