bn.kcv class {bnlearn} | R Documentation |
The bn.kcv class structure
Description
The structure of an object of S3 class bn.kcv
or bn.kcv.list
.
Details
An object of class bn.kcv.list
is a list whose elements are objects
of class bn.kcv
.
An object of class bn.kcv
is a list whose elements correspond to the
iterations of a k-fold cross-validation. Each element contains the following
objects:
-
test
: an integer vector, the indexes of the observations used as a test set. -
fitted
: an object of classbn.fit
, the Bayesian network fitted from the training set. -
learning
: thelearning
element of thebn
object that was used for parameter learning from the training set (either learned from the training set as well or specified by the user). -
loss
: the value of the loss function.
If the loss function requires to predict values from the test sets, each element also contains:
-
predicted
: a factor or a numeric vector, the predicted values for the target node in the test set. -
observed
: a factor or a numeric vector, the observed values for the target node in the test set.
In addition, an object of class bn.kcv
has the following attributes:
-
loss
: a character string, the label of the loss function. -
mean
: the mean of the values of the loss function computed in thek
iterations of the cross-validation, which is printed as the "expected loss" or averaged to compute the "average loss over the runs". -
bn
: either a character string (the label of the learning algorithm to be applied to the training data in each iteration) or an object of classbn
(a fixed network structure).
Author(s)
Marco Scutari