Last chance! 50% off unlimited learning
Sale ends in
Performs cross validation with DIABLO (block.plsda or block.splsda).
DIABLO.cv(x, method = c("mahalanobis.dist", "max.dist", "centroids.dist"),
validation = c("Mfold", "loo"), k = 7, repet = 10, ...)an object of class "sgccda".
criterion used to predict class membership. See perf.
a character giving the kind of (internal) validation to use. See perf.
an integer giving the number of folds (can be re-set internally if needed).
an integer giving the number of times the whole procedure has to be repeated.
other arguments to pass to perf.
number of times the whole procedure was repeated.
number of folds.
kind of validation used.
number of components used.
criterion used to classify individuals of the test sets.
mean classification error rate (based on repet values).
standard error of the classification error rate (based on repet values).
The function uses the weighted predicted classification error rate (see perf).
# NOT RUN {
require(mixOmics)
data(nutrimouse)
data <- list(gene=nutrimouse$gene,lipid=nutrimouse$lipid,Y=nutrimouse$diet)
DIABLO <- block.plsda(X=data,indY=3)
DIABLO.cv(DIABLO)
# }
Run the code above in your browser using DataLab