Locally Weighted Learning

Clicks: 300
ID: 110947
1970
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Abstract
This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, assessing predictions, handling noisy data and outliers, improving the quality of predictions by tuning fit parameters, interference between old and new data, implementing locally weighted learning efficiently, and applications of locally weighted learning. A companion paper surveys how locally weighted learning can be used in robot learning and control.
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atkeson1970artificiallocally Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal;Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal;
Journal artificial intelligence review
Year 1970
DOI
doi:10.1023/A:1006559212014
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