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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

You can install enpls from CRAN:

install.packages("enpls")

Or try the development version on GitHub:

remotes::install_github("nanxstats/enpls")

See vignette("enpls") for a quick-start guide.

Gallery

Feature importance

Outlier detection

Model applicability domain evaluation and ensemble predictive modeling

Contribute

To contribute to this project, please take a look at the Contributing Guidelines first. Please note that the RECA project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('enpls')

Monthly Downloads

311

Version

6.1.1

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/nanxstats/enpls

Homepage

https://nanx.me/enpls/

Maintainer

Nan Xiao

Last Published

July 29th, 2025

Functions in enpls (6.1.1)

Ensemble Sparse Partial Least Squares Regression

enspls.ad.core.fit

core fitting function for enspls.ad

Ensemble Sparse Partial Least Squares for Model Applicability Domain Evaluation

Root Mean Squared Error (RMSE)

Plot enspls.fs object

core function for enspls.fs

core function for enpls.fs

core function for enpls.od

Plot enpls.fs object

Mean Absolute Error (MAE)

predict.enspls.fit

Make Predictions from a Fitted Sparse Ensemble Partial Least Squares Model

predict.enpls.fit

Make Predictions from a Fitted Ensemble Partial Least Squares Model

Plot enpls.ad object

Plot enspls.od object

print.enspls.ad

Print enspls.ad Object

print.enspls.fit

Print Fitted Ensemble Sparse Partial Least Squares Object

logD7.4 Data for 1,000 Compounds

core function for enspls.od

Plot cv.enpls object

Plot enpls.od object

Plot cv.enspls object

Print enpls.od Object

Ensemble Sparse Partial Least Squares for Measuring Feature Importance

Print cv.enpls Object

enspls.fit.core

core function for enspls.fit

print.enpls.fit

Print Fitted Ensemble Partial Least Squares Object

Ensemble Sparse Partial Least Squares for Outlier Detection

Plot enspls.ad object

Print enpls.fs Object

print.cv.enspls

Print cv.enspls Object

Print enpls.ad Object

print.enspls.od

Print enspls.od Object

Add transparency level to hex colors

print.enspls.fs

Print enspls.fs Object

Methylalkanes Retention Index Dataset

enpls.ad.core.pred

core prediction function for enpls.ad

Ensemble Partial Least Squares Regression

Ensemble Partial Least Squares for Model Applicability Domain Evaluation

Cross Validation for Ensemble Partial Least Squares Regression

Cross Validation for Ensemble Sparse Partial Least Squares Regression

Ensemble Partial Least Squares for Measuring Feature Importance

core function for enpls.fit

enpls.ad.core.fit

core fitting function for enpls.ad

enpls: Ensemble Partial Least Squares Regression

Ensemble Partial Least Squares for Outlier Detection

enspls.ad.core.pred

core prediction function for enspls.ad

Root Mean Squared Logarithmic Error (RMSLE)