validate {minet}R Documentation

Inference Validation

Description

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.

Usage

validate( inet, tnet, steps=50 )

Arguments

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.

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.

Value

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.

See Also

minet, vis.res

Examples

data(syn.data)
data(syn.net)
inf.net <- mr.net(build.mim(disc(syn.data)))
table <- validate( inf.net, syn.net, steps=100 )

[Package minet version 1.1.3 Index]