PUlasso: High-Dimensional Variable Selection with Presence-Only Data

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) <arXiv:1711.08129>.

Package details

AuthorHyebin Song [aut, cre], Garvesh Raskutti [aut]
MaintainerHyebin Song <[email protected]>
URL https://arxiv.org/abs/1711.08129
Package repositoryView on CRAN
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PUlasso documentation built on May 2, 2019, 11:40 a.m.