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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

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.

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Version

Install

install.packages('enpls')

Monthly Downloads

255

Version

6.1

License

GPL-3 | file LICENSE

Issues

0

Pull Requests

0

Stars

18

Forks

8

Maintainer

Nan Xiao

Last Published

May 18th, 2019

Functions in enpls (6.1)

enpls.fit

Ensemble Partial Least Squares Regression
cv.enspls

Cross Validation for Ensemble Sparse Partial Least Squares Regression
enpls-package

enpls: Ensemble Partial Least Squares Regression
enspls.ad

Ensemble Sparse Partial Least Squares for Model Applicability Domain Evaluation
enspls.fs

Ensemble Sparse Partial Least Squares for Measuring Feature Importance
enspls.ad.core.fit

core fitting function for enspls.ad
predict.enpls.fit

Make Predictions from a Fitted Ensemble Partial Least Squares Model
predict.enspls.fit

Make Predictions from a Fitted Sparse Ensemble Partial Least Squares Model
print.enspls.fs

Print enspls.fs Object
logd1k

logD7.4 Data for 1,000 Compounds
enspls.od.core

core function for enspls.od
print.enspls.od

Print enspls.od Object
plot.enspls.fs

Plot enspls.fs object
enpls.fs

Ensemble Partial Least Squares for Measuring Feature Importance
enpls.fit.core

core function for enpls.fit
enpls.fs.core

core function for enpls.fs
enpls.mae

Mean Absolute Error (MAE)
print.enpls.ad

Print enpls.ad Object
print.enpls.fit

Print Fitted Ensemble Partial Least Squares Object
rgb2alpha

Add transparency level to hex colors
plot.enspls.od

Plot enspls.od object
enspls.ad.core.pred

core prediction function for enspls.ad
enspls.fit

Ensemble Sparse Partial Least Squares Regression
enspls.fs.core

core function for enspls.fs
alkanes

Methylalkanes Retention Index Dataset
enspls.od

Ensemble Sparse Partial Least Squares for Outlier Detection
plot.enpls.od

Plot enpls.od object
cv.enpls

Cross Validation for Ensemble Partial Least Squares Regression
plot.enspls.ad

Plot enspls.ad object
print.enspls.ad

Print enspls.ad Object
enpls.rmsle

Root Mean Squared Logarithmic Error (RMSLE)
enpls.rmse

Root Mean Squared Error (RMSE)
plot.enpls.ad

Plot enpls.ad object
print.enspls.fit

Print Fitted Ensemble Sparse Partial Least Squares Object
plot.enpls.fs

Plot enpls.fs object
enpls.ad

Ensemble Partial Least Squares for Model Applicability Domain Evaluation
enpls.ad.core.fit

core fitting function for enpls.ad
plot.cv.enpls

Plot cv.enpls object
plot.cv.enspls

Plot cv.enspls object
print.cv.enspls

Print cv.enspls Object
print.cv.enpls

Print cv.enpls Object
print.enpls.fs

Print enpls.fs Object
print.enpls.od

Print enpls.od Object
enpls.od

Ensemble Partial Least Squares for Outlier Detection
enpls.od.core

core function for enpls.od
enpls.ad.core.pred

core prediction function for enpls.ad
enspls.fit.core

core function for enspls.fit