The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
fastadi: Self-Tuning Data Adaptive Matrix Imputation
Implements the AdaptiveImpute matrix completion
algorithm of 'Intelligent Initialization and Adaptive Thresholding for
Iterative Matrix Completion',
<https://amstat.tandfonline.com/doi/abs/10.1080/10618600.2018.1518238>.
AdaptiveImpute is useful for embedding sparsely observed matrices,
often out performs competing matrix completion algorithms, and
self-tunes its hyperparameter, making usage easy.
| Version: |
0.1.1 |
| Depends: |
LRMF3, Matrix, R (≥ 3.1) |
| Imports: |
ellipsis, glue, logger, methods, Rcpp, RSpectra |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
invertiforms, covr, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2022-09-07 |
| Author: |
Alex Hayes  [aut,
cre, cph],
Juhee Cho [aut],
Donggyu Kim [aut],
Karl Rohe [aut] |
| Maintainer: |
Alex Hayes <alexpghayes at gmail.com> |
| BugReports: |
https://github.com/RoheLab/fastadi/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/RoheLab/fastadi |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
fastadi results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=fastadi
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.