bn.kcv.class: The bn.kcv class structure

In jtrecenti/bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

Description

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

Details

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.

• 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.

• 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).

Author(s)

Marco Scutari

jtrecenti/bnlearn documentation built on May 20, 2019, 3:16 a.m.