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hal9001: The Scalable Highly Adaptive Lasso

Authors: Coyle, Jeremy R; Hejazi, Nima S; van der Laan, Mark J;

hal9001: The Scalable Highly Adaptive Lasso

Abstract

A scalable implementation of the highly adaptive lasso algorithm,including routines for constructing sparse matrices of basis functions of the observed data, as well as a custom implementation of Lasso regression tailored to enhance efficiency when the matrix of predictors is composed exclusively of indicator basis functions. For ease of use and increased flexibility, the Lasso fitting routines may invoke code from the glmnet package optionally.

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Keywords

machine learning, semiparametric theory, nonparametric estimation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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