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 ...

Urška Demšar, Paul Harris, Chris Brunsdon, A. Stewart Fotheringham, Sean McLoone, Principal Component Analysis on Spatial Data: An Overview, Annals of the Association of American Geographers, Vol. 103 ...

The first principal component represents the direction of maximum variance, the second principal component is orthogonal to the first and represents the direction of the next highest variance, and so ...

Principal Component Analysis from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...