Functions for computing the ensembles of regularized linear regression estimators defined in Christidis, Lakshmanan, Smucler and Zamar (2017) <arXiv:1712.03561>. The procedure works on top of a given penalized linear regression estimator, the Elastic Net in this implementation, by fitting it to possibly overlapping subsets of features, while at the same time encouraging diversity among the subsets, to reduce the correlations between the predictions that result from each fitted model. The predictions from the models are then aggregated.
|Author||Anthony Christidis <[email protected]>, Ezequiel Smucler <[email protected]>, Ruben Zamar <[email protected]>|
|Maintainer||Ezequiel Smucler <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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