Generalized Principal Component Analysis

07/03/2019

∙

by   F. William Townes, et al.

∙

5

∙

share

Generalized principal component analysis (GLM-PCA) facilitates dimension reduction of non-normally distributed data. We provide a detailed derivation of GLM-PCA with a focus on optimization. We also demonstrate how to incorporate covariates, and suggest post-processing transformations to improve interpretability of latent factors.