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4 votes

What kind of data that I need to do my PCA?

PCA does not require normally distributed data. You should take logs if they make substantive sense (this often happens with variables that relate to money). However, extreme outliers and such can ...
Peter Flom's user avatar
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4 votes

If I do a PCA on centered only variables (of the same unit), does it mean that the principal components created expresses themselves with that unit?

Principle components are linear combinations of the original variables. The first one has the largest variance, the next has the second largest, and so on, subject to a fixed constraint on each set of ...
David Smith's user avatar
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3 votes

Feature selection using backward feature selection in scikit-learn and PCA

First: Doing principal components regression is mostly an alternative to lasso, random forest, and so on, not a preliminary step. Second, lasso is a method of adjusting OLS (or other regressions such ...
Peter Flom's user avatar
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1 vote

Principal Component Analysis and Relation to the SVD of a matrix

Preamble So, as you know singular value decomposition (SVD) decomposed a matrix $X$ (with $i$ rows and $j$ columns) into three matrices: $X = U\Sigma T^T$, where, $U$ is an $i$ x $i$ matrix whose ...
Preston Botter's user avatar

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