Package: PSGD 1.0.6

PSGD: Projected Subset Gradient Descent

Functions to generate ensembles of generalized linear models using a greedy projected subset gradient descent algorithm. The sparsity and diversity tuning parameters are selected by cross-validation.

Authors:Anthony Christidis [aut, cre], Stefan Van Aelst [aut], Ruben Zamar [aut]

PSGD_1.0.6.tar.gz
PSGD_1.0.6.zip(r-4.7-x86_64)PSGD_1.0.6.zip(r-4.7-arm64)PSGD_1.0.6.zip(r-4.6-x86_64)PSGD_1.0.6.zip(r-4.6-arm64)PSGD_1.0.6.zip(r-4.5-x86_64)
PSGD_1.0.6.tgz(r-4.6-x86_64)PSGD_1.0.6.tgz(r-4.6-arm64)PSGD_1.0.6.tgz(r-4.5-x86_64)PSGD_1.0.6.tgz(r-4.5-arm64)
PSGD_1.0.6.tar.gz(r-4.7-arm64)PSGD_1.0.6.tar.gz(r-4.7-x86_64)PSGD_1.0.6.tar.gz(r-4.6-arm64)PSGD_1.0.6.tar.gz(r-4.6-x86_64)
PSGD_1.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PSGD/json (API)

# Install 'PSGD' in R:
install.packages('PSGD', repos = c('https://anthonychristidis.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/anthonychristidis/psgd/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

2.70 score 4 scripts 314 downloads 2 exports 2 dependencies

Last updated from:d20a530bb7. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK166
linux-devel-x86_64OK159
source / vignettesOK251
linux-release-arm64OK184
linux-release-x86_64OK180
macos-release-arm64OK151
macos-release-x86_64OK300
macos-oldrel-arm64OK110
macos-oldrel-x86_64OK238
windows-devel-arm64OK393
windows-devel-x86_64OK288
windows-release-arm64OK244
windows-release-x86_64OK183
windows-oldrel-x86_64OK170
wasm-releaseOK158

Exports:cv.PSGDPSGD

Dependencies:RcppRcppArmadillo