learn.params {bnstruct} | R Documentation |
learn the parameters of a BN.
Description
Learn the parameters of a BN object according to a BNDataset using MAP (Maximum A Posteriori) estimation.
Usage
learn.params(bn, dataset, ess = 1, use.imputed.data = F)
## S4 method for signature 'BN,BNDataset'
learn.params(bn, dataset, ess = 1, use.imputed.data = FALSE)
Arguments
bn |
a |
dataset |
a |
ess |
Equivalent Sample Size value. |
use.imputed.data |
use imputed data. |
Details
Parameter learning is not possible in case of networks learnt using the mmpc
algorithm,
or from bootstrap samples, as there may be loops.
Value
new BN
object with conditional probabilities.
See Also
learn.network
Examples
## Not run:
## first create a BN and learn its structure from a dataset
dataset <- BNDataset("file.header", "file.data")
bn <- BN(dataset)
bn <- learn.structure(bn, dataset)
bn <- learn.params(bn, dataset, ess=1)
## End(Not run)
[Package bnstruct version 1.0.15 Index]