This package implements the LOWESSRF method described by Sage, Genschel, and Nettleton. Random forest prediction weights are iteratively adjusted so that outlying cases are downweighted, resulting in a more robust prediction. Outlying cases are identified using a residual analysis. This approach is motivated by Cleveland's (1979) locally weighted regression and scatterplot smoothing technique.
Package details 


Author  Andrew Sage 
Maintainer  Andrew Sage <[email protected]> 
License  What license is it under? 
Version  1.0.1 
Package repository  View on GitHub 
Installation 
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