Picture Fuzzy Set – Based Approach for Classification

Şuara Onbaşıoğlu Altuhovs; Banu Pazar Varol; Berna Kiraz

doi:10.1007/978-3-032-28997-1_14

Picture Fuzzy Set – Based Approach for Classification

Şuara Onbaşıoğlu Altuhovs
, Banu Pazar Varol^*
, Berna Kiraz

^*Corresponding author for this work

Department of Artificial Intelligence and Data Engineering

Kocaeli University
Piri Reis University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Picture Fuzzy Sets offer a flexible representation for handling uncertainty in data. In this study, we employ a relative frequency – based Picture Fuzzy Set modeling strategy within a k-Nearest Neighbor framework and propose a Picture Fuzzy kNN classifier using the D_α operator. The proposed framework consists of a formal mathematical definition of the relative frequency – based Picture Fuzzy Set representation followed by the algorithmic formulation of the Picture Fuzzy kNN classifier. The proposed method is evaluated on the User Knowledge Modeling dataset and compared with classical kNN using different distance measures and distance-weighting schemes. Experimental results demonstrate that our approach significantly improves classification performance.

Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings
Editors	Barbara Vantaggi, Davide Petturiti, Giulianella Coletti, Thierry Denoeux, Anne Laurent, Enrique Miranda, Jesús Medina, Bernadette Bouchon-Meunier, Ronald R. Yager
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	188-201
Number of pages	14
ISBN (Print)	9783032289964
DOIs	https://doi.org/10.1007/978-3-032-28997-1_14
Publication status	Published - 2026
Event	21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026 - Rome, Italy Duration: 15 Jun 2026 → 19 Jun 2026

Publication series

Name	Communications in Computer and Information Science
Volume	3020 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026
Country/Territory	Italy
City	Rome
Period	15/06/26 → 19/06/26

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Keywords

Classification
k-Nearest Neighbor
Picture Fuzzy kNN
Picture Fuzzy Sets

Access to Document

10.1007/978-3-032-28997-1_14

Cite this

Onbaşıoğlu Altuhovs, Ş., Pazar Varol, B., & Kiraz, B. (2026). Picture Fuzzy Set – Based Approach for Classification. In B. Vantaggi, D. Petturiti, G. Coletti, T. Denoeux, A. Laurent, E. Miranda, J. Medina, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings (pp. 188-201). (Communications in Computer and Information Science; Vol. 3020 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-032-28997-1_14

Onbaşıoğlu Altuhovs, Şuara ; Pazar Varol, Banu ; Kiraz, Berna. / Picture Fuzzy Set – Based Approach for Classification. Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings. editor / Barbara Vantaggi ; Davide Petturiti ; Giulianella Coletti ; Thierry Denoeux ; Anne Laurent ; Enrique Miranda ; Jesús Medina ; Bernadette Bouchon-Meunier ; Ronald R. Yager. Springer Science and Business Media Deutschland GmbH, 2026. pp. 188-201 (Communications in Computer and Information Science).

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Onbaşıoğlu Altuhovs, Ş, Pazar Varol, B & Kiraz, B 2026, Picture Fuzzy Set – Based Approach for Classification. in B Vantaggi, D Petturiti, G Coletti, T Denoeux, A Laurent, E Miranda, J Medina, B Bouchon-Meunier & RR Yager (eds), Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings. Communications in Computer and Information Science, vol. 3020 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 188-201, 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026, Rome, Italy, 15/06/26. https://doi.org/10.1007/978-3-032-28997-1_14

Picture Fuzzy Set – Based Approach for Classification. / Onbaşıoğlu Altuhovs, Şuara; Pazar Varol, Banu; Kiraz, Berna.
Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings. ed. / Barbara Vantaggi; Davide Petturiti; Giulianella Coletti; Thierry Denoeux; Anne Laurent; Enrique Miranda; Jesús Medina; Bernadette Bouchon-Meunier; Ronald R. Yager. Springer Science and Business Media Deutschland GmbH, 2026. p. 188-201 (Communications in Computer and Information Science; Vol. 3020 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Onbaşıoğlu Altuhovs, Şuara

AU - Pazar Varol, Banu

AU - Kiraz, Berna

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

PY - 2026

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N2 - Picture Fuzzy Sets offer a flexible representation for handling uncertainty in data. In this study, we employ a relative frequency – based Picture Fuzzy Set modeling strategy within a k-Nearest Neighbor framework and propose a Picture Fuzzy kNN classifier using the Dα operator. The proposed framework consists of a formal mathematical definition of the relative frequency – based Picture Fuzzy Set representation followed by the algorithmic formulation of the Picture Fuzzy kNN classifier. The proposed method is evaluated on the User Knowledge Modeling dataset and compared with classical kNN using different distance measures and distance-weighting schemes. Experimental results demonstrate that our approach significantly improves classification performance.

AB - Picture Fuzzy Sets offer a flexible representation for handling uncertainty in data. In this study, we employ a relative frequency – based Picture Fuzzy Set modeling strategy within a k-Nearest Neighbor framework and propose a Picture Fuzzy kNN classifier using the Dα operator. The proposed framework consists of a formal mathematical definition of the relative frequency – based Picture Fuzzy Set representation followed by the algorithmic formulation of the Picture Fuzzy kNN classifier. The proposed method is evaluated on the User Knowledge Modeling dataset and compared with classical kNN using different distance measures and distance-weighting schemes. Experimental results demonstrate that our approach significantly improves classification performance.

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KW - Picture Fuzzy Sets

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A2 - Miranda, Enrique

A2 - Medina, Jesús

A2 - Bouchon-Meunier, Bernadette

A2 - Yager, Ronald R.

PB - Springer Science and Business Media Deutschland GmbH

T2 - 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026

Y2 - 15 June 2026 through 19 June 2026

ER -

Onbaşıoğlu Altuhovs Ş, Pazar Varol B, Kiraz B. Picture Fuzzy Set – Based Approach for Classification. In Vantaggi B, Petturiti D, Coletti G, Denoeux T, Laurent A, Miranda E, Medina J, Bouchon-Meunier B, Yager RR, editors, Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings. Springer Science and Business Media Deutschland GmbH. 2026. p. 188-201. (Communications in Computer and Information Science). doi: 10.1007/978-3-032-28997-1_14