tuned.sPLSDA: sPLSDA model after tuning of the number of variables

In singha53/amritr: Accessory Functions Used by Amrit Singh

Description

takes in predited weights and true labels and determines performance characterisitcs

Usage

tuned.sPLSDA(X.train, Y.train, keepXgrid, ncomp, X.test = X.test,
  Y.test = Y.test, filter = filter, topranked = topranked,
  validation = validation, M = M, iter = iter, threads = threads,
  progressBar = progressBar, optimal = optimal,
  errorMethod = errorMethod)

Arguments

keepXgrid	sequence of integers (# of variables to select per component)
ncomp	number of components
M	Number of folds in the cross-validation
X	nxp dataset
Y	vector of phenotype labels with names(Y) == rownames(X)
validatoin	"Mfold" or "loo"

singha53/amritr documentation built on July 21, 2019, 3:46 p.m.