Nothing
library(catnet)
numnodes <- 24
numcats <- 3
maxpars <- 3
cn <- cnRandomCatnet(numnodes, maxpars, numcats)
ps <- cnSamples(cn, 500)
## finds a node with descendants and reduce its number of categories
mpars <- cnMatParents(cn)
for(j in 1:numnodes)
if(sum(mpars[,j]) > 0)
break
if(j < numnodes)
cn@categories[[j]] <- cn@categories[[j]][1:(numcats-1)]
cn <- cnSetProb(cn, ps)
ps <- cnSamples(cn, 500)
res1 <- cnSearchOrder(data=ps, perturbations = NULL,
maxParentSet = maxpars, parentSizes = NULL,
maxComplexity = 0,
nodeOrder = cnOrder(cn),
parentsPool = NULL, fixedParents = NULL,
edgeProb = NULL,
echo = FALSE)
res1
anet1 <- cnFind(res1, cnComplexity(cn))
cnCompare(cn, anet1)
matliks <- matrix(rep(0.5, numnodes*numnodes), nrow=numnodes)
##matliks <- matrix(runif(numnodes*numnodes, 0.49, 0.51), nrow=numnodes)
matliks <- 0.5 + cnMatParents(cn) / 4
res2 <- cnSearchOrder(data=ps, perturbations = NULL,
maxParentSet = maxpars, parentSizes = NULL,
maxComplexity = 0,
nodeOrder = cnOrder(cn),
parentsPool = NULL, fixedParents = NULL,
edgeProb = matliks,
echo = TRUE)
res2
anet2 <- cnFind(res2, cnComplexity(cn))
cnCompare(cn, anet2)
cnCompare(anet1, anet2)
##cnDot(list(cn, anet2), "cn")
sares <- cnSearchSA(data=ps, perturbations=NULL,
maxParentSet=maxpars, parentSizes = NULL,
maxComplexity = 0,
parentsPool = NULL, fixedParents = NULL, edgeProb = matliks,
selectMode = "BIC",
tempStart = 1, tempCoolFact = 0.9, tempCheckOrders = 20,
maxIter = 100, orderShuffles = -1, stopDiff = 1,
numThreads = 2,
priorSearch = NULL,
echo=TRUE)
anet3 <- cnFind(sares, cnComplexity(cn))
cnCompare(cn, anet3)
sares2 <- cnSearchSA(data=ps, perturbations=NULL,
maxParentSet=maxpars, parentSizes = NULL,
maxComplexity = 0,
parentsPool = NULL, fixedParents = NULL, edgeProb = matliks,
selectMode = "BIC",
tempStart = 1, tempCoolFact = 0.9, tempCheckOrders = 20,
maxIter = 100, orderShuffles = -1, stopDiff = 1,
numThreads = 2,
priorSearch = sares,
echo=TRUE)
anet4 <- cnFind(sares2, cnComplexity(cn))
cnCompare(cn, anet4)
mm <- cnSearchHist(data=ps, perturbations=NULL,
maxParentSet=maxpars, parentSizes = NULL,
maxComplexity=0,
parentsPool = NULL, fixedParents = NULL,
selectMode = "BIC",
maxIter = 60, numThreads = 2, echo=TRUE)
matliks <- 0.5 + mm/ (4*max(mm))
mm <- mm > quantile(mm, 0.9)
cnDot(mm, "mm")
mmt <- matliks > quantile(matliks, 0.8)
cnDot(mmt, "mmt")
sares3 <- cnSearchSA(data=ps, perturbations=NULL,
maxParentSet=maxpars, parentSizes = NULL,
maxComplexity = 0,
parentsPool = NULL, fixedParents = NULL, edgeProb = matliks,
selectMode = "BIC",
tempStart = 1, tempCoolFact = 0.9, tempCheckOrders = 20,
maxIter = 100, orderShuffles = -1, stopDiff = 1,
numThreads = 4,
priorSearch = NULL,
echo=TRUE)
anet5 <- cnFind(sares3, cnComplexity(cn))
cnCompare(cn, anet5)
####################################################################################
## effectivelly nil network
library(catnet)
cnet <- cnNew(nodes = c("a", "b", "c"), cats = list(c("1", "2"),
c("1", "2"), c("1", "2")),
parents = list(NULL, c(1), c(1,
2)),
probs = list(c(0.5, 0.5), list(c(0.5, 0.5), c(0.5, 0.5)),
list(list(c(0.5, 0.5), c(0.5, 0.5)), list(c(0.5, 0.5), c(0.5,
0.5)))))
cnet
cnComplexity(cnet)
cnKLComplexity(cnet)
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