training_model: Training bayesian network

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

Description

Training bayesian network

Usage

training_model(
  training_type,
  data,
  number_layers,
  bl,
  wl,
  n_cluster,
  algorithms,
  number_bootstrap = 100,
  debug = FALSE
)

Arguments

training_type	Training type, discrete or continuous
data	Data for training
number_layers	Number of bayesian network layer
bl	List of blacklist
wl	List of whitelist
n_cluster	Number of core for training
algorithms	Algorithms for learning network structure and parameters
number_bootstrap	Number of bootstrap
debug	Debug mode

Value

An object list of trained model and training parameters

Examples

library(wrmbn)
data("preprocessed")
training_type <- preprocessed$type
data <- preprocessed$data
number_layers <- preprocessed$desire_layers
bl <- bl_wl$blacklist
wl <- bl_wl$whitelist
n_cluster <- 4
algorithms <- c("gs", "hc", "tabu", "iamb", "inter.iamb", "fast.iamb")
algorithms <- c("hc", "tabu")
trained_models <- training_model(training_type, data, number_layers, bl, wl, n_cluster, algorithms, number_bootstrap = 500, debug = FALSE)

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