sci
Locally Weighted Projection Regression (LWPR) is a recent algorithm
that achieves nonlinear function approximation in high dimensional spaces
with redundant and irrelevant input dimensions. At its core, it uses
locally linear models, spanned by a small number of univariate regressions in
selected directions in input space. A locally weighted variant of
Partial Least Squares (PLS) is employed for doing the dimensionality
reduction.