Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification

The paper proposes a taxonomy for categorizing the main features of the supervised learning classification problems and a notation for the identification of the supervised learning classification problem categories. The proposed taxonomy has been based on the review and analysis of the recent litera...

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Autores principales:	Ireneusz Czarnowski, Piotr Jedrzejowicz
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Machine learning supervised classification classification problems taxonomy of features notation for problem description Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/949fd29db5b3467c9f010874df36d164
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id	oai:doaj.org-article:949fd29db5b3467c9f010874df36d164
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spelling	oai:doaj.org-article:949fd29db5b3467c9f010874df36d1642021-11-17T00:00:19ZSupervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification2169-353610.1109/ACCESS.2021.3125622https://doaj.org/article/949fd29db5b3467c9f010874df36d1642021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9605652/https://doaj.org/toc/2169-3536The paper proposes a taxonomy for categorizing the main features of the supervised learning classification problems and a notation for the identification of the supervised learning classification problem categories. The proposed taxonomy has been based on the review and analysis of the recent literature. It allowed the construction of the landscape of decision problem factors influencing the supervised learning processes. To enable a concise and coherent identification of supervised classification problems we have suggested a notation enabling description and identification of various supervised learning classification problem types and their critical features. The notation consists of 5 fields representing, in a sequence, a structure and properties of decision classes, structural model and properties of attributes, features of the data source, and the performance measure used for constructing and evaluating a classifier. The proposed notation is open and could be extended in the case of need new developments within the machine learning theory.Ireneusz CzarnowskiPiotr JedrzejowiczIEEEarticleMachine learningsupervised classificationclassification problemstaxonomy of featuresnotation for problem descriptionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 151386-151400 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Machine learning supervised classification classification problems taxonomy of features notation for problem description Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Machine learning supervised classification classification problems taxonomy of features notation for problem description Electrical engineering. Electronics. Nuclear engineering TK1-9971 Ireneusz Czarnowski Piotr Jedrzejowicz Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
description	The paper proposes a taxonomy for categorizing the main features of the supervised learning classification problems and a notation for the identification of the supervised learning classification problem categories. The proposed taxonomy has been based on the review and analysis of the recent literature. It allowed the construction of the landscape of decision problem factors influencing the supervised learning processes. To enable a concise and coherent identification of supervised classification problems we have suggested a notation enabling description and identification of various supervised learning classification problem types and their critical features. The notation consists of 5 fields representing, in a sequence, a structure and properties of decision classes, structural model and properties of attributes, features of the data source, and the performance measure used for constructing and evaluating a classifier. The proposed notation is open and could be extended in the case of need new developments within the machine learning theory.
format	article
author	Ireneusz Czarnowski Piotr Jedrzejowicz
author_facet	Ireneusz Czarnowski Piotr Jedrzejowicz
author_sort	Ireneusz Czarnowski
title	Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
title_short	Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
title_full	Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
title_fullStr	Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
title_full_unstemmed	Supervised Classification Problems–Taxonomy of Dimensions and Notation for Problems Identification
title_sort	supervised classification problems–taxonomy of dimensions and notation for problems identification
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/949fd29db5b3467c9f010874df36d164
work_keys_str_mv	AT ireneuszczarnowski supervisedclassificationproblemsx2013taxonomyofdimensionsandnotationforproblemsidentification AT piotrjedrzejowicz supervisedclassificationproblemsx2013taxonomyofdimensionsandnotationforproblemsidentification
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Supervised Classification Problems&#x2013;Taxonomy of Dimensions and Notation for Problems Identification

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