enpls-package: enpls: Ensemble Partial Least Squares Regression
In enpls: Ensemble Partial Least Squares Regression
Description
Author(s)
See Also
Description
An algorithmic framework for measuring feature importance,
outlier detection, model applicability domain evaluation,
and ensemble predictive modeling with (sparse)
partial least squares regressions.
Author(s)
Maintainer: Nan Xiao me@nanx.me (0000-0002-0250-5673)
Authors:
Dong-Sheng Cao
Miao-Zhu Li miaozhu.li@duke.edu
Qing-Song Xu qsxu@csu.edu.cn
See Also
Useful links:
-
-
Report bugs at https://github.com/nanxstats/enpls/issues
enpls documentation built on May 18, 2019, 9:02 a.m.
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Description Author(s) See Also
Description
An algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.
Author(s)
Maintainer: Nan Xiao me@nanx.me (0000-0002-0250-5673)
Authors:
Dong-Sheng Cao
Miao-Zhu Li miaozhu.li@duke.edu
Qing-Song Xu qsxu@csu.edu.cn
See Also
Useful links:
Report bugs at https://github.com/nanxstats/enpls/issues
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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