Comparing the predictive power of decision tree models with different tuning approaches on Hungarian Myocardial Infarction Registry

Peter Piros, Rita Fleiner, Tamas Ferenci, Levente Kovacs, A. Jánosi

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

Abstract

In this comparative study authors investigated if a difference exists in the predictive power of decision tree models tuned with different resampling methods. K-fold cross validation, repeated cross validation and bootstrap were used to find the optimal parameters for each model on the dataset of Hungarian Myocardial Infarction Registry. The target variable was the 1year mortality and the differences were measured in 10 different cases with different number of records on randomly selected, real-world datasets. Results show that a relatively small difference exists, and an order can be established between the resampling methods: cross validation was slightly outperformed repeated cross validation and both had better results than models trained with bootstrap.

Original languageEnglish
Title of host publicationSACI 2019 - IEEE 13th International Symposium on Applied Computational Intelligence and Informatics, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages326-331
Number of pages6
ISBN (Electronic)9781728106854
DOIs
Publication statusPublished - May 2019
Event13th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2019 - Timisoara, Romania
Duration: May 29 2019May 31 2019

Publication series

NameSACI 2019 - IEEE 13th International Symposium on Applied Computational Intelligence and Informatics, Proceedings

Conference

Conference13th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2019
CountryRomania
CityTimisoara
Period5/29/195/31/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Health Informatics

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  • Cite this

    Piros, P., Fleiner, R., Ferenci, T., Kovacs, L., & Jánosi, A. (2019). Comparing the predictive power of decision tree models with different tuning approaches on Hungarian Myocardial Infarction Registry. In SACI 2019 - IEEE 13th International Symposium on Applied Computational Intelligence and Informatics, Proceedings (pp. 326-331). [9111525] (SACI 2019 - IEEE 13th International Symposium on Applied Computational Intelligence and Informatics, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SACI46893.2019.9111525