| conf.mat {BDgraph} | R Documentation |
Create a Confusion Matrix.
conf.mat( pred, actual, cutoff = 0.5, proportion = FALSE,
dnn = c( "Prediction", "Actual" ), ... )
pred |
adjacency matrix corresponding to an estimated graph.
It can be an object with |
actual |
adjacency matrix corresponding to the actual graph structure in which a_{ij}=1 if there is a link between notes i and j, otherwise a_{ij}=0.
It can be an object with |
cutoff |
cutoff value for the case that |
proportion |
logical: FALSE (default) for a confusion matrix with number of cases. TRUE, for a confusion matrix with the proportion of cases. |
dnn |
names to be given to the dimensions in the result (the dimnames names). |
... |
further arguments to be passed to |
the results of table on pred and actual.
Reza Mohammadi a.mohammadi@uva.nl
conf.mat.plot, compare, roc, bdgraph
## Not run: set.seed( 100 ) # Generating multivariate normal data from a 'random' graph data.sim <- bdgraph.sim( n = 50, p = 6, size = 7, vis = TRUE ) # Running sampling algorithm based on GGMs sample.ggm <- bdgraph( data = data.sim, method = "ggm", iter = 10000 ) # Confusion Matrix for GGM method conf.mat( pred = sample.ggm, actual = data.sim ) ## End(Not run)