# evaluate: Inference Evaluation

## Description

`evaluate`

compares the inferred network to the true
underlying network for several threshold values and appends the
resulting confusion matrices to the returned object.## Usage

evaluate(inf.net,true.net,sym=TRUE,extend=0)

## Arguments

inf.net

An adjacency matrix representing the inferred
network.

true.net

An adjacency matrix representing the true
underlying network.

sym

Logical, make a symmetric evaluation
(default = TRUE).

extend

Integer, specifying the desired number of links to
extend in the network (default=0)

## Value

`evaluate`

returns a matrix with four columns representing
`TP,FP,TN,FN`

.
These values are computed for each of the predicted links that
should be sorted. Thus, each row of the returned object contains
the confusion matrix as a function of the cutoff in the edgelist.

## Details

The first edgelist network `inet`

is compared to the true
underlying network, `tnet`

, in order to compute the
metrics of the performance.
If extend is specified, `extend`

links that network
`inet`

has set to 0 are added to the inferred network
randomly at the end of the edgelist.## Examples

# Inference
inf.net <- cor(syntren300.data)
#Evaluate
table <- evaluate(inf.net, syntren300.net)
table.nosym <- evaluate(inf.net, syntren300.net,sym=FALSE)