A collection of methods for 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. | |