enpls (5.8)

0 users

Ensemble Partial Least Squares Regression.

https://enpls.org
https://github.com/road2stat/enpls
http://cran.r-project.org/web/packages/enpls

An algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.

Maintainer: Nan Xiao
Author(s): Nan Xiao [aut, cre], Dongsheng Cao [aut], Miaozhu Li [aut], Qingsong Xu [aut]

License: GPL-3 | file LICENSE

Uses: doParallel, foreach, ggplot2, plotly, pls, reshape2, spls, knitr, rmarkdown

Released about 1 month ago.


8 previous versions

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of enpls yet. Want to be the first? Write one now.


Related packages: AnalyzeFMRI, CellularAutomaton, PET, PTAk, TIMP, WilcoxCV, bvls, chemCal, clustvarsel, compositions, drc, drm, elasticnet, fastICA, fmri, homals, kohonen, leaps, lspls, minpack.lm(20 best matches, based on common tags.)


Search for enpls on google, google scholar, r-help, r-devel.

Visit enpls on R Graphical Manual.