mlscorecheck: Testing the consistency of reported performance scores and experiments in machine learning-Reference-Cited by-同舟云学术

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mlscorecheck: Testing the consistency of reported performance scores and experiments in machine learning

Published:2024-05 Issue: Volume:583 Page:127556
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Kovács György^ORCID,Fazekas Attila^ORCID

Publisher

Elsevier BV

Reference19 articles.

1. Classification assessment methods;Tharwat;Appl. Comput. Inform.,2020

2. Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling;Vandewiele;Artif. Intell. Med.,2021

3. Statistical errors in clinical studies;Slutsky;J. Wrist Surg.,2013

4. Leakage and the reproducibility crisis in machine-learning-based science;Kapoor;Patterns,2023

5. Artificial intelligence faces reproducibility crisis;Hutson;Science,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Testing the consistency of performance scores reported for binary classification problems;Applied Soft Computing;2024-10

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