Dimensionality Reduction

Modules
	Principal Component Analysis
	Produces a model that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables called principal components.
	Principal Component Projection
	Projects a higher dimensional data point to a lower dimensional subspace spanned by principal components learned through the PCA training procedure.

Detailed Description

A collection of methods for dimensionality reduction.