mFGS-BS (majority rule and Fast Greedy equivalence Search with Bayesian Scoring)

The algorithm is from the journal "Hybrid Bayesian network discovery with latent variables by scoring multiple interventions". https://link.springer.com/article/10.1007/s10618-022-00882-9

Name		Name	Last commit message	Last commit date
Latest commit History 26 Commits
.Rproj.user		.Rproj.user
Data		Data
TestINT		TestINT
archieved		archieved
.gitattributes		.gitattributes
.gitignore		.gitignore
ALARM_MAGtrue_L10.csv		ALARM_MAGtrue_L10.csv
README.md		README.md
Rplot.pdf		Rplot.pdf
Rplot01.pdf		Rplot01.pdf
alarm_L5_full_10k.csv		alarm_L5_full_10k.csv
causal-cmd.log		causal-cmd.log
checkDependencies.R		checkDependencies.R
converttotetraddot.R		converttotetraddot.R
generate_data.R		generate_data.R
graph1.txt		graph1.txt
graphutils.R		graphutils.R
impossibly_long_graph_file_name_temporary.txt		impossibly_long_graph_file_name_temporary.txt
interventFGES.Rproj		interventFGES.Rproj
interventional_data_alarm_FGES_v7_method1-1.R		interventional_data_alarm_FGES_v7_method1-1.R
mFGES-BS_data_alarm.R		mFGES-BS_data_alarm.R
myoutput.txt		myoutput.txt
pc.cons.intern2.R		pc.cons.intern2.R
posteriorcal.R		posteriorcal.R
posteriorcal3.R		posteriorcal3.R
precisionrecall.R		precisionrecall.R
precisionrecall_undirected_edge.R		precisionrecall_undirected_edge.R
remove_weak_cycle.R		remove_weak_cycle.R
test_bicscore.rda		test_bicscore.rda
trainingData_ALARM_L10_10k.csv		trainingData_ALARM_L10_10k.csv
trainingData_ALARM_L5_100k.csv		trainingData_ALARM_L5_100k.csv
trainingData_ALARM_L5_10k.csv		trainingData_ALARM_L5_10k.csv
trainingData_ALARM_N_100k.csv		trainingData_ALARM_N_100k.csv
trainingData_ALARM_N_10k.csv		trainingData_ALARM_N_10k.csv

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