bm_pls_pcr {tsensembler} | R Documentation |
Fit PLS/PCR regression models
Description
Learning aPartial Least Squares or Principal Components Regression from training data
Usage
bm_pls_pcr(form, data, lpars)
Arguments
form |
formula |
data |
data to train the model |
lpars |
parameter setting: For this multivariate regression model the main parameter is "method". The available options are "kernelpls", "svdpc", "cppls", "widekernelpls", and "simpls" |
Details
Parameter setting can vary in method
See mvr
for a comprehensive description.
Imports learning procedure from pls package.
See Also
other learning models: bm_mars
;
bm_ppr
; bm_gbm
;
bm_glm
; bm_cubist
;
bm_randomforest
; bm_gaussianprocess
;
bm_ffnn
; bm_svr
Other base learning models:
bm_cubist()
,
bm_ffnn()
,
bm_gaussianprocess()
,
bm_gbm()
,
bm_glm()
,
bm_mars()
,
bm_ppr()
,
bm_randomforest()
,
bm_svr()
[Package tsensembler version 0.1.0 Index]