lwpr
The Locally Weighted Projection Regression Library
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.
homepage ↗ sourceforge: lwpr
Available in
| Overlay | Newest | Ebuilds | Last activity | |
|---|---|---|---|---|
| science gitweb ↗ | 1.2.5 | 1 | 4 d | details › |
Versions & arches
Use flags of 1.2.5
- examples Install examples, usually source code
- octave Add sci-mathematics/octave support
- static-libs Build static versions of dynamic libraries as well
- doc Add extra documentation (API, Javadoc, etc). It is recommended to enable per package instead of globally