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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("road2stat/enpls")

To load the package in R, simply use

library("enpls")

and you are all set. See the vignette (or open with vignette("enpls") in R) for a quick-start guide.

Links

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Version

Install

install.packages('enpls')

Monthly Downloads

214

Version

5.6

License

GPL (>= 2)

Maintainer

Nan Xiao

Last Published

November 26th, 2016

Functions in enpls (5.6)

enpls.ad.core.fit

core fitting function for enpls.ad
enpls.fs.core

core function for enpls.fs
enpls.fit.core

core function for enpls.fit
enpls.ad.core.pred

core prediction function for enpls.ad
enspls.ad

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

core function for enspls.fit
enpls.rmse

Root Mean Squared Error (RMSE)
enpls.rmsle

Root Mean Squared Logarithmic Error (RMSLE)
enpls.od.core

core function for enpls.od
enpls.od

Ensemble Partial Least Squares for Outlier Detection
enspls.ad.core.fit

core fitting function for enspls.ad
enspls.ad.core.pred

core prediction function for enspls.ad
plot.cv.enspls

Plot cv.enspls object
plot.cv.enpls

Plot cv.enpls object
enspls.fit

Ensemble Sparse Partial Least Squares Regression
enspls.fs.core

core function for enspls.fs
plot.enpls.ad

Plot enpls.ad object
predict.enpls.fit

Make Predictions from a Fitted Ensemble Partial Least Squares Model
plot.enpls.fs

Plot enpls.fs object
predict.enspls.fit

Make Predictions from a Fitted Sparse Ensemble Partial Least Squares Model
print.enpls.ad

Print enpls.ad Object
print.enpls.fit

Print Fitted Ensemble Partial Least Squares Object
print.enspls.od

Print enspls.od Object
print.enspls.fs

Print enspls.fs Object
rgb2alpha

Add transparency level to hex colors
enspls.fs

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

core function for enspls.od
print.cv.enpls

Print cv.enpls Object
enpls.fs

Ensemble Partial Least Squares for Measuring Feature Importance
print.cv.enspls

Print cv.enspls Object
enspls.od

Ensemble Sparse Partial Least Squares for Outlier Detection
enpls.mae

Mean Absolute Error (MAE)
plot.enpls.od

Plot enpls.od object
logd1k

logD7.4 Data for 1,000 Compounds
plot.enspls.ad

Plot enspls.ad object
print.enspls.ad

Print enspls.ad Object
print.enspls.fit

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

Plot enspls.fs object
print.enpls.fs

Print enpls.fs Object
plot.enspls.od

Plot enspls.od object
print.enpls.od

Print enpls.od Object
enpls.fit

Ensemble Partial Least Squares Regression
alkanes

Methylalkanes Retention Index Dataset
enpls.ad

Ensemble Partial Least Squares for Model Applicability Domain Evaluation
cv.enspls

Cross Validation for Ensemble Sparse Partial Least Squares Regression
cv.enpls

Cross Validation for Ensemble Partial Least Squares Regression
enpls-package

Ensemble Partial Least Squares Regression