v 3.2.5 Updated: 4 months, 3 weeks ago

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.


To install R-PUlasso, paste this in macOS terminal after installing MacPorts

sudo port install R-PUlasso

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