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A Library for Locally Weighted Projection Regression

By Stefan Klanke, Sethu Vijayakumar and Stefan Schaal

Abstract

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

Topics: regression, local learning, online learning, C, Matlab, C++, Octave, Python
Year: 2010
OAI identifier: oai:www.era.lib.ed.ac.uk:1842/3665
Journal:

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Citations

  1. (1994). An interpretation of partial least squares. doi
  2. Octave is a free Matlab clone available at http://www.octave.org. We tested our library against version 2.9.12.

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