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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #87091 A study on the statistical evaluation of classifiers
sameAs	A study on the statistical evaluation of classifiers
http://eprints.org/ontology/hasAccepted	A study on the statistical evaluation of classifiers (PDF)
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dc:hasVersion	A study on the statistical evaluation of classifiers (PDF)
Title	A study on the statistical evaluation of classifiers
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2020-11-27
Creator	Alexandre Plastino Nadine M. Neumann A. Freitas Jony A. Pinto Junior
status	peer reviewed published
Publisher	Cambridge University Press
abstract	Statistical significance analysis, based on hypothesis tests, is a common approach for comparing classifiers. However, many studies oversimplify this analysis by simply checking the condition p-value < 0.05, ignoring important concepts such as the effect size and the statistical power of the test. This problem is so worrying that the American Statistical Association has taken a strong stand on the subject, noting that although the p-value is a useful statistical measure, it has been abusively used and misinterpreted. This work highlights problems caused by the misuse of hypothesis tests and shows how the effect size and the power of the test can provide important information for better decision-making. To investigate these issues, we perform empirical studies with different classifiers and 50 datasets, using the Student’s t-test and the Wilcoxon test to compare classifiers. The results show that an isolated p-value analysis can lead to wrong conclusions and that the evaluation of the effect size and the power of the test contributes to a more principled decision-making.
Is Part Of	Knowledge Engineering Review https://kar.kent.ac.uk/id/repository
Subject	Q335 Artificial intelligence
list of authors	https://kar.kent.ac.uk/id/eprint/87091#authors
issue	e1
volume	36
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #87091 A study on the statistical evaluation of classifiers

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