Visualizing the decision rules behind the ROC curves: understanding the classification process-Reference-Cited by-同舟云学术

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Visualizing the decision rules behind the ROC curves: understanding the classification process

Published:2020-11-13 Issue:1 Volume:105 Page:135-161
ISSN:1863-8171
Container-title:AStA Advances in Statistical Analysis
language:en
Short-container-title:AStA Adv Stat Anal

Author:

Pérez-Fernández Sonia^ORCID,Martínez-Camblor Pablo^ORCID,Filzmoser Peter^ORCID,Corral Norberto^ORCID

Funder

Gobierno del Principado de Asturias

Universidad de Oviedo

Ministerio de Economía y Competitividad

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Economics and Econometrics,Social Sciences (miscellaneous),Modeling and Simulation,Statistics and Probability,Analysis

Link

http://link.springer.com/content/pdf/10.1007/s10182-020-00385-2.pdf

Reference31 articles.

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2. Bamber, D.: The area above the ordinal dominance graph and the area below the receiver operating characteristic graph. J. Math. Psychol. 12(4), 387–415 (1975). https://doi.org/10.1016/0022-2496(75)90001-2

3. Biau, G., Bunea, F., Wegkamp, M.H.: Functional classification in Hilbert spaces. IEEE Trans. Inf. Theory 51(6), 2163–2172 (2005). https://doi.org/10.1109/TIT.2005.847705

4. Chen, B., Li, P., Qin, J., Yu, T.: Using a monotonic density ratio model to find the asymptotically optimal combination of multiple diagnostic tests. J. Am. Stat. Assoc. 111(514), 861–874 (2016). https://doi.org/10.1080/01621459.2015.1066681

5. Fisher, R.A.: The use of multiple measurements in taxonomic problems. Ann. Eugen. 7, 179–188 (1936). https://doi.org/10.1111/j.1469-1809.1936.tb02137.x

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