Technical note: Incorporating expert domain knowledge into causal structure discovery workflows

Jarmo Samuli Mäkelä, Laila Melkas, Ivan Mammarella, Tuomo Nieminen, Suyog Halasinamara Chandramouli, Rafael Savvides, Kai Puolamäki

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Sammanfattning

In this note, we argue that the outputs of causal discovery algorithms should not usually be considered end results but rather starting points and hypotheses for further study. The incentive to explore this topic came from a recent study by Krich et al. (2020), which gives a good introduction to estimating causal networks in biosphere–atmosphere interaction but confines the scope by investigating the outcome of a single algorithm. We aim to give a broader perspective to this study and to illustrate how not only different algorithms but also different initial states and prior information of possible causal model structures affect the outcome. We provide a proof-of-concept demonstration of how to incorporate expert domain knowledge with causal structure discovery and remark on how to detect and take into account over-fitting and concept drift.
Originalspråkengelska
TidskriftBiogeosciences
Volym19
Nummer8
Sidor (från-till)2095-2099
Antal sidor5
ISSN1726-4170
DOI
StatusPublicerad - 19 apr. 2022
MoE-publikationstypA1 Tidskriftsartikel-refererad

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