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The PCA and SPCA Tutorial is back.

This is an improved and updated legacy tutorial on Principal Component Analysis (PCA) and one of its variants, Standardized PCA (SPCA). Both are techniques for identifying unknown trends in multidimensional data sets.

Despite the fact that one can find online many tutorials on PCA, undergraduate and graduate students are rarely exposed to the algorithm.

On the other hand, the fact that SVD can be used in both PCA and LSI (LSA) have induced some to assume, that PCA is LSI. Actually, PCA is neither LSI (LSA) nor Factor Analysis. Why? Good question. Check the tutorial at