### Set up java parameter and load rmcfs package
options(java.parameters = "-Xmx4g")
library(rmcfs)
# create input data
adata <- artificial.data(rnd.features = 10)
info(adata)
# Parametrize and run MCFS-ID procedure
result <- mcfs(class~., adata, projections = 200, projectionSize = 4,
cutoffPermutations = 5, finalCV = FALSE, finalRuleset = FALSE,
threadsNumber = 2)
# build interdependencies graph (all default parameters).
gid <- build.idgraph(result)
plot(gid)
# build interdependencies graph for top 6 features
# and top 12 interdependencies and plot all nodes
gid <- build.idgraph(result, size = 6, size_ID = 12, plot_all_nodes = TRUE)
plot(gid, label.dist = 1)Run the code above in your browser using DataLab