Package: FSDAM 2024.7-30

FSDAM: Forward Stepwise Deep Autoencoder-Based Monotone NLDR

FS-DAM performs feature extraction through latent variables identification. Implementation is based on autoencoders with monotonicity and orthogonality constraints.

Authors:Youyi Fong [cre], Jun Xu [aut]

FSDAM_2024.7-30.tar.gz
FSDAM_2024.7-30.zip(r-4.5)FSDAM_2024.7-30.zip(r-4.4)FSDAM_2024.7-30.zip(r-4.3)
FSDAM_2024.7-30.tgz(r-4.4-any)FSDAM_2024.7-30.tgz(r-4.3-any)
FSDAM_2024.7-30.tar.gz(r-4.5-noble)FSDAM_2024.7-30.tar.gz(r-4.4-noble)
FSDAM_2024.7-30.tgz(r-4.4-emscripten)FSDAM_2024.7-30.tgz(r-4.3-emscripten)
FSDAM.pdf |FSDAM.html✨
FSDAM/json (API)

# Install 'FSDAM' in R:

install.packages('FSDAM', repos = c('https://youyifong.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cc.505 - Select Biomarkers from the HVTN 505 Correlates Analysis
hvtn505tier1 - HVTN 505 Immune Correlates Tier 1 Dataset

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.30 score 3 scripts 192 downloads 2 exports 13 dependencies

Last updated 4 months agofrom:1b0d1eeccd. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 30 2024
R-4.5-win	OK	Oct 30 2024
R-4.5-linux	OK	Oct 30 2024
R-4.4-win	OK	Oct 30 2024
R-4.4-mac	OK	Oct 30 2024
R-4.3-win	OK	Oct 30 2024
R-4.3-mac	OK	Oct 30 2024