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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Vydané v:	IEEE transactions on knowledge and data engineering Ročník 32; číslo 8; s. 1586 - 1594
Hlavní autori:	Wong, Tzu-Tsung, Yeh, Po-Yang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	<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
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