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

Efficient algorithm for solving PU (Positive and Unlabelled) 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 (2017) <arXiv:1711.08129>.

Package details

AuthorHyebin Song [aut, cre], Garvesh Raskutti [aut]
MaintainerHyebin Song <[email protected]>
LicenseGPL-2
Version3.1.1
URL https://arxiv.org/abs/1711.08129
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("PUlasso")

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PUlasso documentation built on May 15, 2018, 9:03 a.m.