Principal Components: Properties & Applications

In course

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Description

This lecture covers the definition and properties of principal components, including population and sample principal components, covariance matrix, and eigenvectors. It also discusses the correlation structure, choice of components, and graphical representations. The instructor explains the proportion of variance explained by each component and provides insights on testing hypotheses about principal components.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_fmh8p0k2

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

Mathematics

Algebra: Linear algebra

Information engineering

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