Reliable Accuracy Estimates from k-Fold Cross Validation

It is popular to evaluate the performance of classification algorithms by k -fold cross validation. A reliable accuracy estimate will have a relatively small variance, and several studies therefore suggested to repeatedly perform k -fold cross validation. Most of them did not consider the correlatio...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 32; H. 8; S. 1586 - 1594
Hauptverfasser:	Wong, Tzu-Tsung, Yeh, Po-Yang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k -fold cross validation Accuracy Algorithms Classification Classification algorithms Correlation Dependence Dependency relationship Estimates Forests Journalists Performance evaluation Reliability reliable estimate replication Roads Statistical analysis Statistical methods Testing Urban areas Variance Vocabulary development
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
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