Learn R Programming

bnlearn (version 4.7.1)

bn.kcv class: The bn.kcv class structure

Description

The structure of an object of S3 class bn.kcv or bn.kcv.list.

Arguments

Author

Marco Scutari

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 class bn.fit, the Bayesian network fitted from the training set.

  • learning: the learning element of the bn 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 the k 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 class bn (a fixed network structure).