Monotonicity Detection and Enforcement in Longitudinal Classification-Reference-Cited by-同舟云学术

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Monotonicity Detection and Enforcement in Longitudinal Classification

Published:2019 Issue: Volume: Page:63-77
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Ovchinnik Sergey,Otero Fernando E. B.,Freitas Alex A.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-34885-4_5

Reference20 articles.

1. Ben-David, A.: Monotonicity maintenance in information-theoretic machine learning algorithms. Mach. Learn. 19(1), 29–43 (1995). https://doi.org/10.1023/a:1022655006810

2. Ben-David, A., Sterling, L., Tran, T.: Adding monotonicity to learning algorithms may impair their accuracy. Expert Syst. Appl. 36(3), 6627–6634 (2009). https://doi.org/10.1016/j.eswa.2008.08.021

3. Lecture Notes in Computer Science;J Brookhouse,2016

4. Cano, J.R., Gutiérrez, P.A., Krawczyk, B., Woźniak, M., García, S.: Monotonic classification: an overview on algorithms, performance measures and data sets. Neurocomputing 341, 168–182 (2019). https://doi.org/10.1016/j.neucom.2019.02.024

5. Chen, C.C., Li, S.T.: Credit rating with a monotonicity-constrained support vector machine model. Expert Syst. Appl. 41(16), 7235–7247 (2014)

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1. Nested trees for longitudinal classification;Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing;2022-04-25

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