The Annals of Statistics, Vol. 36, No. 6, High Dimensional Inference and Random Matrices (Dec., 2008), pp. 2791-2817 (27 pages) Principal component analysis (PCA) is a standard tool for dimensional ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 68, No. 1 (2006), pp. 109-126 (18 pages) Functional data analysis is intrinsically infinite dimensional; functional ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

Principal component analysis (PCA) simplifies the complexity in high-dimensional data while retaining trends and patterns. It does this by transforming the data into fewer dimensions, which act as ...