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.

Version: 2020.11-18
Depends: R (≥ 3.5.0)
Imports: kyotil, reticulate (≥ 1.10)
Suggests: R.rsp, RUnit
Published: 2020-11-20
Author: Youyi Fong [cre], Jun Xu [aut]
Maintainer: Youyi Fong <youyifong at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: FSDAM results


Reference manual: FSDAM.pdf
Vignettes: Fitting Threshold Regression Models Using chngpt
Package source: FSDAM_2020.11-18.tar.gz
Windows binaries: r-devel: FSDAM_2020.11-18.zip, r-release: FSDAM_2020.11-18.zip, r-oldrel: FSDAM_2020.11-18.zip
macOS binaries: r-release (arm64): FSDAM_2020.11-18.tgz, r-release (x86_64): FSDAM_2020.11-18.tgz, r-oldrel: FSDAM_2020.11-18.tgz


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