Description Objects from the Class Slots Extends Methods Author(s) References See Also Examples
This class of objects contains the information describing a cross validation experiment, i.e. its settings.
Objects can be created by calls of the form CV(...)
providing the values for the class slots.
These objects include information on the number of repetitions of the
cross validation (CV) experiment, the number of folds, the random number generator seed,
whether the sampling should or not be stratified and optionally, the
concrete data splits to use on each repetition and iteration of the CV
experiment. Note that most of the times you will not supply these data
splits as the CV routines in this infra-structure will take care of
building them. Still, this allows you to replicate some experiment
carried out with specific train/test splits.
nReps
:Object of class numeric
indicating
the number of repetitions of the N folds CV experiment (defaulting
to 1).
nFolds
:Object of class numeric
with the
number of folds on each CV experiment (defaulting to 10).
strat
:Object of class logical
indicating
whether the sampling should or not be stratified (defaulting to FALSE).
seed
:Object of class numeric
with the
random number generator seed (defaulting to 1234).
dataSplits
:Object of class list
containing the data splits to use on each repetition of a
k-folds CV experiment (defaulting to NULL
). This list
should contain nReps x nFolds
elements. Each element should be a
vector with the row ids of the test set of the respective
iteration. For instance, on a 3 x 10-fold CV experiment the 10th
element should contain the ids of the test cases of the 10th fold
of the first repetition and the 11th element the ids of the test
cases on the 1st fold of the 2nd repetition. On all these
iterations the training set will be formed by the ids not
appearing in the test set.
Class EstCommon
, directly.
Class EstimationMethod
, directly.
signature(object = "CV")
: method used to
show the contents of a CV
object.
Luis Torgo ltorgo@dcc.fc.up.pt
Torgo, L. (2014) An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R. arXiv:1412.0436 [cs.MS] http://arxiv.org/abs/1412.0436
MonteCarlo
,
LOOCV
,
Bootstrap
,
Holdout
,
EstimationMethod
,
EstimationTask
1 2 3 4 5 6 7 8 9 10 11 12 | showClass("CV")
## the defaults (1 x 10-fold CV)
s <- CV()
## stratified 2 x 5-fold CV
s1 <- CV(nReps=2,nFolds=5,strat=TRUE)
## Small example illustrating the format of user supplied data splits.
## This could be a 3-fold CV process of a data set with 30 cases
s2 <- CV(dataSplits=list(1:10,11:20,21:30))
s2
|
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