Fuzzy k-nearest neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise-Reference-Cited by-同舟云学术

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Fuzzy k-nearest neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise

Published:2021-06 Issue: Volume:439 Page:106-121
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

González Sergio,García Salvador,Li Sheng-Tun,John Robert,Herrera Francisco

Funder

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference40 articles.

1. Evolutionary fuzzy rule-based methods for monotonic classification;Alcalá-Fdez;IEEE Trans. Fuzzy Syst.,2017

2. Automatic generation of symbolic multiattribute ordinal knowledge-based dsss: methodology and applications;Ben-David;Decis. Sci.,1992

3. Monotonicity maintenance in information-theoretic machine learning algorithms;Ben-David;Mach. Learn.,1995

4. Adding monotonicity to learning algorithms may impair their accuracy;Ben-David;Expert Syst. Appl.,2009

5. Time for a change: a tutorial for comparing multiple classifiers through bayesian analysis;Benavoli;J. Mach. Learn. Res.,2017

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