compare-methods: Some basic criteria of comparison between actual and inferred...

Description Value Methods Author(s) Examples

Description

Allows comparison between actual and inferred network.

Value

A vector containing : sensitivity, predictive positive value, the usual F-score (2*ppv*sens/(sppvpe+sens)), the 1/2 ponderated Fscore ((1+0.5^2)*ppv*sens/(ppv/4+sens)) and the 2 ponderated Fscore ((1+2^2)*ppv*sens/(ppv*4+sens)).

Methods

signature(Net = "network", Net_inf = "network", nv = "numeric")
Net

A network object containing the actual network.

Net_inf

A network object containing the inferred network.

nv

A number that indicates at which level of cutoff the comparison should be done.

Author(s)

Bertrand Frederic, Myriam Maumy-Bertrand.

Examples

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data(Net)
data(Net_inf_PL)

#Comparing true and inferred networks
Crit_values=NULL

#Here are the cutoff level tested
test.seq<-seq(0,max(abs(Net_inf_PL@network*0.9)),length.out=200)
for(u in test.seq){
	Crit_values<-rbind(Crit_values,Patterns::compare(Net,Net_inf_PL,u))
}
matplot(test.seq,Crit_values,type="l",ylab="Criterion value",xlab="Cutoff level",lwd=2)
legend(x="topleft", legend=colnames(Crit_values), lty=1:5,col=1:5,ncol=2,cex=.9)

fbertran/Patterns documentation built on Dec. 4, 2019, 1:12 p.m.