A Library for Locally Weighted Projection Regression

In this paper we introduce an improved implementation of locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high-dimensional input data. As the key features, our code supports multi-threading, is available for multiple platforms, and provides wrappers for several programming languages.

• Type: Journal
• Year: 2008
• Where: JMLR
• Authors: Stefan Klanke, Sethu Vijayakumar, Stefan Schaal
• Keywords: Improved Implementation, JMLR 2008, Supervised Learning, Weighted Projection Regression