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 289 downloads 2 exports 2 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-arm64OK182
linux-devel-x86_64OK173
source / vignettesOK226
linux-release-arm64OK172
linux-release-x86_64OK175
macos-release-arm64OK165
macos-release-x86_64OK425
macos-oldrel-arm64OK135
macos-oldrel-x86_64OK242
windows-devel-arm64OK254
windows-devel-x86_64OK269
windows-release-arm64OK225
windows-release-x86_64OK211
windows-oldrel-x86_64OK197
wasm-releaseOK193

Exports:cv.PSGDPSGD

Dependencies:RcppRcppArmadillo