Editing Principal component analysis (section)

== See also ==
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* [[Correspondence analysis]] (for contingency tables)
* [[Multiple correspondence analysis]] (for qualitative variables)
* [[Factor analysis of mixed data]] (for quantitative '''and''' qualitative variables)
* [[Canonical correlation]]
* [[CUR matrix approximation]] (can replace of low-rank SVD approximation)
* [[Detrended correspondence analysis]]
* [[Directional component analysis]]
* [[Dynamic mode decomposition]]
* [[Eigenface]]
* [[Expectation–maximization algorithm]]
* [[v:Exploratory factor analysis|Exploratory factor analysis]] (Wikiversity)
* [[Factorial code]]
* [[Functional principal component analysis]]
* [[Geometric data analysis]]
* [[Independent component analysis]]
* [[Kernel PCA]]
* [[L1-norm principal component analysis]]
* [[Low-rank approximation]]
* [[Matrix decomposition]]
* [[Non-negative matrix factorization]]
* [[Nonlinear dimensionality reduction]]
* [[Oja's rule]]
* [[Point distribution model]] (PCA applied to morphometry and computer vision)
* [[b:Statistics/Multivariate Data Analysis/Principal Component Analysis|Principal component analysis]] (Wikibooks)
* [[Principal component regression]]
* [[Singular spectrum analysis]]
* [[Singular value decomposition]]
* [[Sparse PCA]]
* [[Transform coding]]
* [[Weighted least squares]]
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