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Measurement Science Review

The Journal of Institute of Measurement Science of Slovak Academy of Sciences

6 Issues per year


IMPACT FACTOR 2016: 1.344

CiteScore 2016: 1.88

SCImago Journal Rank (SJR) 2016: 0.495
Source Normalized Impact per Paper (SNIP) 2016: 1.419

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1335-8871
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Volume 15, Issue 4

Issues

Comparison of the Effects of Cross-validation Methods on Determining Performances of Classifiers Used in Diagnosing Congestive Heart Failure

Yalcin Isler
  • Department of Biomedical Engineering, Izmir Katip Celebi Univertsity, Balatcik Campus, 35620, Izmir, Turkey
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Ali Narin
  • Department of Electrical and Electronics Engineering, Bulent Ecevit University, Incivez, 67100, Zonguldak, Turkey
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mahmut Ozer
  • Department of Electrical and Electronics Engineering, Bulent Ecevit University, Incivez, 67100, Zonguldak, Turkey
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-08-27 | DOI: https://doi.org/10.1515/msr-2015-0027

Abstract

Congestive heart failure (CHF) occurs when the heart is unable to provide sufficient pump action to maintain blood flow to meet the needs of the body. Early diagnosis is important since the mortality rate of the patients with CHF is very high. There are different validation methods to measure performances of classifier algorithms designed for this purpose. In this study, k-fold and leave-one-out cross-validation methods were tested for performance measures of five distinct classifiers in the diagnosis of the patients with CHF. Each algorithm was run 100 times and the average and the standard deviation of classifier performances were recorded. As a result, it was observed that average performance was enhanced and the variability of performances was decreased when the number of data sections used in the cross-validation method was increased.

Keywords: Heart rate variability; heart failure; cross-validation; classification.

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About the article

Received: 2014-08-18

Accepted: 2015-08-05

Published Online: 2015-08-27

Published in Print: 2015-08-01


Citation Information: Measurement Science Review, Volume 15, Issue 4, Pages 196–201, ISSN (Online) 1335-8871, DOI: https://doi.org/10.1515/msr-2015-0027.

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© by Yalcin Isler. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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