@misc{10481/78172,
year = {2022},
month = {10},
url = {https://hdl.handle.net/10481/78172},
abstract = {This paper presents the first review of noise models in classification covering both label and
attribute noise. Their study reveals the lack of a unified nomenclature in this field. In order to address
this problem, a tripartite nomenclature based on the structural analysis of existing noise models is
proposed. Additionally, a revision of their current taxonomies is carried out, which are combined
and updated to better reflect the nature of any model. Finally, a categorization of noise models is
proposed from a practical point of view depending on the characteristics of noise and the study
purpose. These contributions provide a variety of models to introduce noise, their characteristics
according to the proposed taxonomy and a unified way of naming them, which will facilitate their
identification and study, as well as the reproducibility of future research.},
publisher = {MDPI},
keywords = {Noise models},
keywords = {Nomenclature},
keywords = {Taxonomy},
keywords = {Noisy data},
keywords = {Classification},
title = {Noise Models in Classification: Unified Nomenclature, Extended Taxonomy and Pragmatic Categorization},
doi = {10.3390/math10203736},
author = {Sáez Muñoz, José Antonio},
}