Principal Components as a Small Number of Interpretable Variables: Some Examples
The original purpose of PCA was to reduce a large number (p) of variables to a much small number (m) of PCs whilst retaining as much as possible of the variation in the p original variables. The technique is especially useful if m « p,and if the m PCs can be readily interpreted.
KeywordsComponent Number Crowded Condition Anatomical Measurement Stock Market Price Basic Amenity
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