Investigating the effect of binning on causal discovery

Andrew Colt Deckert, Erich Kummerfeld

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Binning (a.k.a. discretization) of numerically continuous measurements is a wide-spread but controversial practice in data collection, analysis, and presentation. The consequences of binning have been evaluated for many different kinds of data analysis methods, however so far the effect of binning on causal discovery algorithms has not been directly investigated. This paper reports the results of a simulation study that examined the effect of binning on the Greedy Equivalence Search (GES) causal discovery algorithm. Our findings suggest that unbinned continuous data often result in the highest search performance, but some exceptions are identified. We also found that binned data are more sensitive to changes in sample size and tuning parameters, and identified some interactive effects between sample size, binning, and tuning parameter on performance.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
EditorsIllhoi Yoo, Jinbo Bi, Xiaohua Tony Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2574-2581
Number of pages8
ISBN (Electronic)9781728118673
DOIs
StatePublished - Nov 2019
Event2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States
Duration: Nov 18 2019Nov 21 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

Conference

Conference2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019
CountryUnited States
CitySan Diego
Period11/18/1911/21/19

Bibliographical note

Funding Information:
This work was supported by funding from NCRR 1UL1TR002494-01 to EK.

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Causal Discovery
  • Data discretization
  • Greedy Equivalence Search (GES)
  • Search Performance

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