Demixed PCA (dPCA)

A supervised variant of PCA that finds a subspace maximally explaining one labeled variable's variance (e.g. an answer identity) while separating it from other variables (e.g. a query's string length), imported from neuroscience population-coding analysis; its null space can then be used to selectively remove one variable's information via projection.