validate {minet} | R Documentation |
validate
compares the infered network to the true underlying network for several threshold values
and appends the resulting confusion matrix for each threshold to the returned object.
validate( inet, tnet, steps=50 )
inet |
infered network - see minet . |
tnet |
the true underlying network. This network must have the same size and variable names as inet . |
steps |
the number of threshold values to be used in the validation process - see details . |
For each of the steps
threshold values T, the edges whose weight are (strictly)
below T are eliminated. All the other edges will have a weight 1. Each resulting graph
is compared to the true underlying network in order to get steps
confusion matrices.
validate
returns a data frame whith four columns named thrsh, tp, fp, fn
. These values are
computed for each of the steps
thresholds. Thus each row of the returned object contains
the confusion matrix for a different threshold.
data(syn.data) data(syn.net) inf.net <- mr.net(build.mim(disc(syn.data))) table <- validate( inf.net, syn.net, steps=100 )