Description Usage Arguments Examples
Perform a k-fold cross-validation using the function bn.cv and scan every node to estimate its posterior classification error.
1 2 3 4 5 6 7 8 9 | tronco.kfold.posterr(
x,
models = names(as.models(x)),
events = as.events(x),
runs = 10,
k = 10,
cores.ratio = 1,
silent = FALSE
)
|
x |
A reconstructed model (the output of tronco.capri) |
models |
The names of the selected regularizers (bic, aic or caprese) |
events |
a list of event |
runs |
a positive integer number, the number of times cross-validation will be run |
k |
a positive integer number, the number of groups into which the data will be split |
cores.ratio |
Percentage of cores to use. coresRate * (numCores - 1) |
silent |
A parameter to disable/enable verbose messages. |
1 2 | data(test_model)
tronco.kfold.posterr(test_model, k = 2, runs = 2, cores.ratio = 0)
|
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