Bayesian network structure learning algorithm used by pyAgrum.BNLearner

[pgr-me]

After looking over the code and reading two of the papers on aGrUM / pyAgrum, I'm not sure which structure learning algorithm is used by pyAgrum.BNLearner. The paper aGrUM: A Graphical Universal model framework indicates "greedy hill climbing, local search with tabu list and K2".

...After reviewing the code, it looks like the above algorithms are in the BN/learning folder.

...And tracing the code back, there is a block of code that allows the user to select an algorithm: K2, GREEDY_HILL_CLIMBING, LOCAL_SEARCH_WITH_TABU_LIST, MICC.

Ah - I found where to specify the learning algorithm.

import pandas as pd
import pyAgrum as gum

data = pd.read_csv("path/to/data.csv")
bn = gum.BNLearner(data)
bn.useK2([1, 2, 3])  # Or MIIC, GreedyHillClimbing, etc.

I think I'm good!

[phwuil]

Hi @pgr-me ,

you found it ! :-)
We could be more prolix here but you can find these functions.

... And one more thing : you can check the state of a learner by printing it !