Index | Topics |
score-based algorithms {bnlearn} | R Documentation |
Score-based structure learning algorithms
Description
Learn the structure of a Bayesian network using a hill-climbing (HC) or a Tabu search (TABU) greedy search.
Usage
hc(x, start = NULL, whitelist = NULL, blacklist = NULL, score = NULL, ...,
debug = FALSE, restart = 0, perturb = 1, max.iter = Inf, maxp = Inf, optimized = TRUE)
tabu(x, start = NULL, whitelist = NULL, blacklist = NULL, score = NULL, ...,
debug = FALSE, tabu = 10, max.tabu = tabu, max.iter = Inf, maxp = Inf, optimized = TRUE)
Arguments
x |
a data frame containing the variables in the model. |
start |
an object of class |
whitelist |
a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs to be included in the graph. |
blacklist |
a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs not to be included in the graph. |
score |
a character string, the label of the network score to be used in the algorithm. If none is
specified, the default score is the Bayesian Information Criterion for both discrete and
continuous data sets. See |
... |
additional tuning parameters for the network score. See |
debug |
a boolean value. If |
restart |
an integer, the number of random restarts. |
tabu |
a positive integer number, the length of the tabu list used in the |
max.tabu |
a positive integer number, the iterations tabu search can perform without improving the best network score. |
perturb |
an integer, the number of attempts to randomly insert/remove/reverse an arc on every random restart. |
max.iter |
an integer, the maximum number of iterations. |
maxp |
the maximum number of parents allowed for a node in any network that is considered in the search,
including that that is returned. The default value is |
optimized |
a boolean value. If |
Value
An object of class bn
. See bn-class
for
details.
Note
See structure learning
for a complete list of
structure learning algorithms with the respective references.
Author(s)
Marco Scutari
See Also
network scores
, constraint-based algorithms, hybrid algorithms, local
discovery algorithms, alpha.star.
Index | Topics |