Table 1 Available functions of the package minet (version 1.1.6)
Function | Usage |
|---|---|
minet(data, method, estimator, disc, nbins) | Network inference from data |
discretize(data, disc, nbins) | Unsupervised discretization |
build.mim(data, estimator) | Mutual information matrix estimation Estimator can be ""mi.empirical","mi.mm","mi.shrink" and "mi.sg". |
mrnet(mim) | MRNET algorithm |
aracne(mim) | ARACNE algorithm |
clr(mim) | CLR algorithm |
norm(net) | matrix/network normalization |
validate(net1, net2, steps) | Computes confusion matrices |
pr(table) | Computes precisions and recalls from confusion matrices |
rates(table) | Computes true positive rates and false positive rates from confusion matrices |
show.pr(table) | Displays precision-recall curves from confusion matrices |
show.roc(table) | Displays receiver operator caracteristic curves from confusion matrices |
fscores(table) | Returns a vector of F β -scores from confusion matrices |