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

2020

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.

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