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.
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, run the following command in macOS terminal (Applications->Utilities->Terminal)
sudo port install R-PUlasso
To see what files were installed by R-PUlasso, run:
port contents R-PUlasso
To later upgrade R-PUlasso, run:
sudo port selfupdate && sudo port upgrade R-PUlasso
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