## Locally Weighed Projection Regression

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.
More information on the library page.
Parameters available here:

- Generation Threshold: decides when to add an additional receptive field
- Learning Rate: influences the adaptation rate for online learning
- Receptive Field Width: initial width for receptive field generation