TabuList

class otagrum.TabuList(*args)

TabuList learner.

Parameters:

data2-d sequence of float

The data

initial_dag: :class:`~otagrum.NamedDAG`

The Initial DAG for the algorithm

max_parentsint

Maximum parents that a node can have

restartsint

Number of random restarts

tabu_list_sizeint

Size of the TABU list

Notes

The TABU list algorithm is used with the BIC score and Gaussian copulas to learn the structure of a CBN from data. Moreover, it uses the decomposition of BIC score to avoid computing score over the entire graph.

Methods

getBestScore()	Returns the final score value.
getMaxParents()	Returns the value of the parameter max_parents.
getRestarts()	Returns the value of the parameter restarts.
getVerbosity()	Returns the verbosity flag value.
learnDAG()	Learn the DAG from data.
setCMode(cmode)	Changes the copula model (Bernstein or Gaussian) used for computing the BIC score.
setVerbosity(verbose)	Change the value of verbosity flag.

__init__(*args)

getBestScore()

Returns the final score value.

Returns:

scoredouble

Final score value

getMaxParents()

Returns the value of the parameter max_parents.

Returns:

max_parentsint

Maximum number of parents

getRestarts()

Returns the value of the parameter restarts.

Returns:

restartsint

Restarts value

getVerbosity()

Returns the verbosity flag value.

Returns:

verbosebool

Verbosity flag value

learnDAG()

Learn the DAG from data.

Returns:

dagNamedDAG

the learned DAG

Notes

This step starts with the learned PDAG and orient the remaining undirected edges by avoiding to add new V-structures unless it implies to create an oriented circle.

setCMode(cmode)

Changes the copula model (Bernstein or Gaussian) used for computing the BIC score.

Returns:

verboseCorrectedMutualInformation.CModeTypes

Copula model (Gaussian or Bernstein)

setVerbosity(verbose)

Change the value of verbosity flag.

Parameters:

verbosebool

New verbosity flag value. If True, a lot of details about the learning procedure are printed.