trainPLS2: Train PLS for train dataset by cross-validation

In chengvt/cheng: cheng

Description

Train PLS for train dataset by cross-validation. This is different from trainPLS as you have to specify the preprocessing method manually.

Usage

trainPLS2(x, y, newx = NULL, newy = NULL, maxncomp = 20,
  cvsegments = 10, round = 2, reduceVar = TRUE, cycles = 3,
  ncomp = c("auto", "manual", "fixed"), fixedncomp = NULL,
  prepro = c("mc", "norm_mc", "au"), threshold = 0.02, saveModel = FALSE)

Arguments

x	predictor matrix
y	prediction target vector
maxncomp	maximum ncomp for calculation
cvsegments	refer to mvrCv's segments argument
round	round numbers
reduceVar	variable reduction using VIP
cycles	cycles for variable reduction
ncomp	'auto','manual' or 'fixed'
fixedncomp	fixed numerical value
prepro	preprocessing method. Choose from c("mc", "norm_mc","au"). Default to "mc" if not specified.
threshold	threshold for selecting ncomp

chengvt/cheng documentation built on May 13, 2019, 3:52 p.m.