groupbn_refine_manually: groupbn_refine_manually

In GroupBN: Inferring Group Bayesian Networks using Hierarchical Feature Clustering

Description

Based on a GroupBN, a cluster can be selected manually, that is split and the refined model is learned.

Usage

groupbn_refine_manually(res, hierarchy, refine, arc.thresh=NULL,
R=100, debug=FALSE, seed=NULL)

Arguments

res	an object of class groupbn
hierarchy	a cluster object from ClustOfVar
refine	name of group to be refined
arc.thresh	threshold for bootstrap arcs
R	number of bootstrap replicates for model averaging, default is 100
debug	a boolean, if TRUE, debugging messages are printed
seed	a random seed number

Value

returns an object of class groupbn

Author(s)

Ann-Kristin Becker

Examples

#load example data
data(wine)
wine.test<-wine[wine$Soil%in%c("Reference", "Env1"),1:29]
wine.test$Soil<-factor(wine.test$Soil)
levels(wine.test$Soil)<-c("0", "1")

#cluster data
hierarchy<-hclustvar(X.quanti=wine.test[,3:29], X.quali=wine.test[,1:2])

#Learn group network among 5 clusters with "Soil" as target variable
wine.groupbn<-groupbn(hierarchy, k=5, target="Soil", separate=NULL,
X.quanti=wine.test[,3:29], X.quali=wine.test[,1:2], seed=321)

#Refine cluster 2
wine.groupbn.refined<-groupbn_refine_manually(wine.groupbn, hierarchy,
refine = "cl2", seed=321)

#Plot refined network
plot(wine.groupbn.refined)

GroupBN documentation built on March 7, 2021, 5:06 p.m.