# An FCA-based Approach to Direct Edges in a Causal Bayesian Network: A Pilot Study using a Surgery Data Set

### Walisson Ferreira, Mark Song, Luis Zarate

#### Abstract

One of the problems during the construction of Causal Bayesian Network based on constraint algorithms occurs when it is not possible to orient edges between nodes due to Markov Equivalence. In this scenario this article presents the use of Formal Concept Analysis (FCA), specially attributes implication, as an alternative to support the definition of the direction of the edges. To do this it was applied algorithms of Bayesian learners (PC) and FCA in a data set containing 12 attributes and 5,473 records of surgeries performed in Belo Horizonte - Brazil. According to the results, although attribute implication did not necessarily mean causality, the implication rules were useful in defining edges orientation on the Bayesian network learned by PC Algorithm. The results of FCA were validated through intervention using do-calculus and by an expert in the domain. Therefore, as result of this paper, it is presented a heuristic to direct edges between nodes when the direction is unknown.

Download#### Paper Citation

#### in Harvard Style

Ferreira W., Song M. and Zarate L. (2020). **An FCA-based Approach to Direct Edges in a Causal Bayesian Network: A Pilot Study using a Surgery Data Set**.In *Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,* ISBN 978-989-758-423-7, pages 116-123. DOI: 10.5220/0009392101160123

#### in Bibtex Style

@conference{iceis20,

author={Walisson Ferreira and Mark Song and Luis Zarate},

title={An FCA-based Approach to Direct Edges in a Causal Bayesian Network: A Pilot Study using a Surgery Data Set},

booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},

year={2020},

pages={116-123},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0009392101160123},

isbn={978-989-758-423-7},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,

TI - An FCA-based Approach to Direct Edges in a Causal Bayesian Network: A Pilot Study using a Surgery Data Set

SN - 978-989-758-423-7

AU - Ferreira W.

AU - Song M.

AU - Zarate L.

PY - 2020

SP - 116

EP - 123

DO - 10.5220/0009392101160123