Roweis Discriminant Analysis: A Generalized Subspace Learning Method

Understand

We present a new method which generalizes subspace learning based on eigenvalue and generalized eigenvalue problems.

• This method, Roweis Discriminant Analysis (RDA), is named after Sam Roweis to whom the field of subspace learning owes significantly.
• RDA is a family of infinite number of algorithms where Principal Component Analysis (PCA), Supervised PCA (SPCA), and Fisher Discriminant Analysis (FDA) are special cases.
• One of the extreme special cases, which we name Double Supervised Discriminant Analysis (DSDA), uses the labels twice; it is novel and has not appeared elsewhere.