Description
Ensemble Partial Least Squares Regression.
Description
An algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.
README.md
enpls 
enpls offers an algorithmic framework for measuring feature importance, outlier detection, model applicability domain evaluation, and ensemble predictive modeling with (sparse) partial least squares regressions.
Installation
Install enpls from CRAN:
install.packages("enpls")
Or try the development version on GitHub:
# install.packages("devtools")
devtools::install_github("nanxstats/enpls")
See the vignette (or open with vignette("enpls") in R) for a quick-start guide.
Gallery
Measuring Feature Importance
Outlier Detection
Model Applicability Domain Evaluation / Ensemble Predictive Modeling
Contribute
To contribute to this project, please take a look at the Contributing Guidelines first. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.