plGridMulti(array.train, array.valid = NULL, ctrlFS, top, how, aucSkip = FALSE, verbose = TRUE, ...)
ExprsMulti
object to use as training set.ExprsMulti
object to use as validation set.ctrlFeatureSelect
.top = 0
to include all features. Note that providing a numeric vector
for the top
argument will have plGrid
search across multiple
top features. However, by providing a list of numeric vectors as the top
argument, the user can force the default handling of numeric vectors.build
method to iterate.calcStats
.exprso-predict
.how
method. Unlike the build
method,
plGrid
allows multiple parameters for each argument, supplied as a vector.
See Details.ExprsPipeline-class
object.
plGrid
, the plGridMulti
function accepts a ctrlFS
argument, allowing for 1-vs-all classification with implicit feature selection.
1-vs-all classification, this function divides the data into 1-vs-all bins,
performs a 1-vs-all feature selection for each bin, and then performs a 1-vs-all
classification for that same bin. As such, each ExprsMachine
within the
ExprsModule
will have its own unique feature selection history.Take note, that plGridMulti
does not have built-in plCV
support.
To use plGridMulti
with cross-validation, use plNested
.
fs
build
doMulti
exprso-predict
plCV
plGrid
plGridMulti
plMonteCarlo
plNested