learn_dbn_struc {dbnR} | R Documentation |
Learns the structure of a markovian n DBN model from data
Description
Learns a gaussian dynamic Bayesian network from a dataset. It allows the creation of markovian n nets rather than only markov 1.
Usage
learn_dbn_struc(dt, size = 2, method = "dmmhc", f_dt = NULL, ...)
Arguments
dt |
the data.frame or data.table to be used |
size |
number of time slices of the net. Markovian 1 would be size 2 |
method |
the structure learning method of choice to use |
f_dt |
previously folded dataset, in case some specific rows have to be removed after the folding |
... |
additional parameters for |
Value
a "dbn" S3 object with the structure of the network
Examples
data("motor")
net <- learn_dbn_struc(motor, size = 3)
[Package dbnR version 0.7.9 Index]