Modelling Interactions in High-Dimensional Data with Backtracking

Implementation of the algorithm introduced in Shah, R. D. (2016) < http://www.jmlr.org/papers/volume17/13-515/13-515.pdf>. Data with thousands of predictors can be handled. The algorithm performs sequential Lasso fits on design matrices containing increasing sets of candidate interactions. Previous fits are used to greatly speed up subsequent fits so the algorithm is very efficient.


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install.packages("LassoBacktracking")

0.1.2 by Rajen Shah, 2 years ago


www.jmlr.org/papers/volume17/13-515/13-515.pdf


Browse source code at https://github.com/cran/LassoBacktracking


Authors: Rajen Shah [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Matrix, parallel, Rcpp

Linking to Rcpp


See at CRAN