The area under the ROC curve as a measure of clustering quality-Reference-Cited by-同舟云学术

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The area under the ROC curve as a measure of clustering quality

Published:2022-04-26 Issue:3 Volume:36 Page:1219-1245
ISSN:1384-5810
Container-title:Data Mining and Knowledge Discovery
language:en
Short-container-title:Data Min Knowl Disc

Author:

Jaskowiak Pablo A.^ORCID,Costa Ivan G.,Campello Ricardo J. G. B.

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Interdisciplinary Center for Clinical Research

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s10618-022-00829-0.pdf

Reference64 articles.

1. Amigó E, Gonzalo J, Artiles J, Verdejo F (2009) A comparison of extrinsic clustering evaluation metrics based on formal constraints. Inf Retr 12(5):613

2. Arbelaitz O, Gurrutxaga I, Muguerza J, Pérez JM, Perona I (2013) An extensive comparative study of cluster validity indices. Pattern Recognit 46(1):243–256

3. Baker FB, Hubert LJ (1975) Measuring the power of hierarchical cluster analysis. J Am Stat Assoc 70(349):31–38

4. Bezdek JC, Pal NR (1998) Some new indexes of cluster validity. IEEE Trans Syst, Man Cybern, Part B 28(3):301–315

5. Bradley AP (1997) The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recognit 30(7):1145–1159

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