Articles | Volume 19, issue 8
https://doi.org/10.5194/bg-19-2095-2022
https://doi.org/10.5194/bg-19-2095-2022
Technical note
 | 
19 Apr 2022
Technical note |  | 19 Apr 2022

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

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

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Cited articles

Akaike, H.: A new look at the statistical model identification, IEEE T. Automat. Contr., 19, 716–723, https://doi.org/10.1109/TAC.1974.1100705, 1974. a
Bergmeir, C. and Benítez, J. M.: On the use of cross-validation for time series predictor evaluation, Information Sciences, 191, 192–213, https://doi.org/10.1016/j.ins.2011.12.028, 2012. a
Chickering, D. M.: Optimal Structure Identification with Greedy Search, J. Mach. Learn. Res., 3, 507–554, https://doi.org/10.1162/153244303321897717, 2003. a
Colombo, D. and Maathuis, M. H.: Order-Independent Constraint-Based Causal Structure Learning, J. Mach. Learn. Res., 15, 3741–3782, 2014. a, b
Druzdzel, M. J.: The role of assumptions in causal discovery, in: Workshop on Uncertainty Processing (WUPES-09), University of Pittsburgh, 57–68, http://d-scholarship.pitt.edu/6017/ (last access: 6 April 2022), 2009. a
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Causal structure discovery algorithms have been making headway into Earth system sciences, and they can be used to increase our understanding on biosphere–atmosphere interactions. In this paper we present a procedure on how to utilize prior knowledge of the domain experts together with these algorithms in order to find more robust causal structure models. We also demonstrate how to avoid pitfalls such as over-fitting and concept drift during this process.
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