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enpls: Ensemble Partial Least Squares Regression
An algorithmic framework for measuring feature importance,
outlier detection, model applicability domain evaluation,
and ensemble predictive modeling with (sparse)
partial least squares regressions.
| Version: |
6.1 |
| Depends: |
R (≥ 3.0.2) |
| Imports: |
pls, spls, foreach, doParallel, ggplot2, reshape2, plotly |
| Suggests: |
knitr, rmarkdown |
| Published: |
2019-05-18 |
| Author: |
Nan Xiao  [aut,
cre],
Dong-Sheng Cao [aut],
Miao-Zhu Li [aut],
Qing-Song Xu [aut] |
| Maintainer: |
Nan Xiao <me at nanx.me> |
| BugReports: |
https://github.com/nanxstats/enpls/issues |
| License: |
GPL-3 | file LICENSE |
| URL: |
https://nanx.me/enpls/, https://github.com/nanxstats/enpls |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| In views: |
ChemPhys |
| CRAN checks: |
enpls results |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=enpls
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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.
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