cross_validation_learning_algorithms: Cross validation for learning bayesian network

In bayes-modeling/wrmbn: Water Resource Management using Bayesian Network

Description

Cross validation for learning bayesian network

Usage

cross_validation_learning_algorithms(
  data,
  algorithms,
  wl,
  bl,
  target,
  k_fold = 5,
  runs = 10,
  loss = "mse",
  n_cluster = NULL,
  debug = NULL
)

Arguments

data	Processed data frame for learning bayesian network
algorithms	Algorithms for cross validation
wl	Network white list
bl	Network black list
target	A character string, the label of target node for prediction
k_fold	The data are split in k subsets of equal size
runs	A positive integer number, the number of times k-fold or hold-out cross-validation will be run.
loss	A character string, the label of a loss function, detail see https://cran.r-project.org/web/packages/bnlearn/bnlearn.pdf
n_cluster	an optional cluster object from package parallel.
debug	Debug mode

Value

Cross validation result for each algorithm

bayes-modeling/wrmbn documentation built on Dec. 19, 2021, 6:45 a.m.