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

^*Bu çalışma için yazışmadan sorumlu yazar

Yapay Zeka ve Veri Mühendisliği Bölümü

Kocaeli University
Piri Reis University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Information Processing and Management of Uncertainty in Knowledge-Based Systems - 21st International Conference, IPMU 2026, Proceedings
Editörler	Barbara Vantaggi, Davide Petturiti, Giulianella Coletti, Thierry Denoeux, Anne Laurent, Enrique Miranda, Jesús Medina, Bernadette Bouchon-Meunier, Ronald R. Yager
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	188-201
Sayfa sayısı	14
ISBN (Basılı)	9783032289964
DOI'lar	https://doi.org/10.1007/978-3-032-28997-1_14
Yayın durumu	Yayınlandı - 2026
Etkinlik	21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026 - Rome, Italy Süre: 15 Haz 2026 → 19 Haz 2026

Yayın serisi

Adı	Communications in Computer and Information Science
Hacim	3020 CCIS
ISSN (Basılı)	1865-0929
ISSN (Elektronik)	1865-0937

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???event.eventtypes.event.conference???	21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026
Ülke/Bölge	Italy
Şehir	Rome
Periyot	15/06/26 → 19/06/26

Bibliyografik not

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

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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; Hac. 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. editör / 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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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 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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note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026 ; Conference date: 15-06-2026 Through 19-06-2026",

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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, hac. 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; Hac. 3020 CCIS).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Picture Fuzzy Set – Based Approach for Classification

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

Y1 - 2026

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.

KW - Classification

KW - k-Nearest Neighbor

KW - Picture Fuzzy kNN

KW - Picture Fuzzy Sets

UR - https://www.scopus.com/pages/publications/105042284666

U2 - 10.1007/978-3-032-28997-1_14

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

M3 - Conference contribution

AN - SCOPUS:105042284666

SN - 9783032289964

T3 - Communications in Computer and Information Science

SP - 188

EP - 201

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

A2 - Vantaggi, Barbara

A2 - Petturiti, Davide

A2 - Coletti, Giulianella

A2 - Denoeux, Thierry

A2 - Laurent, Anne

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, editörler, 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