PUlasso (3.2.3)

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High-Dimensional Variable Selection with Presence-Only Data.

https://arxiv.org/abs/1711.08129
http://cran.r-project.org/web/packages/PUlasso

Efficient algorithm for solving PU (Positive and Unlabeled) problem in low or high dimensional setting with lasso or group lasso penalty. The algorithm uses Maximization-Minorization and (block) coordinate descent. Sparse calculation and parallel computing are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2018) .

Maintainer: Hyebin Song
Author(s): Hyebin Song [aut, cre], Garvesh Raskutti [aut]

License: GPL-2

Uses: doParallel, foreach, ggplot2, Matrix, Rcpp, testthat, knitr, rmarkdown

Released 5 months ago.


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