Implements the SISAL algorithm by Tikka and Hollmén. It is a sequential backward selection algorithm which uses a linear model in a crossvalidation setting. Starting from the full model, one variable at a time is removed based on the regression coefficients. From this set of models, a parsimonious (sparse) model is found by choosing the model with the smallest number of variables among those models where the validation error is smaller than a threshold. Also implements extensions which explore larger parts of the search space and/or use ridge regression instead of ordinary least squares.
Package details 


Author  Mikko Korpela [aut, cre] 
Date of publication  20151010 15:45:32 
Maintainer  Mikko Korpela <[email protected]> 
License  GPL (>= 2) 
Version  0.46 
Package repository  View on CRAN 
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