Extended Possibilistic Fuzzification for Classification

Robert K. Nowicki, Janusz T. Starczewski, Rafał Grycuk

2019

Abstract

In this paper, the extended possibilistic fuzzification for classification is proposed. Similar approach with the use of fuzzy–rough fuzzification (Nowicki and Starczewski, 2017; Nowicki, 2019) allows to obtain one of three decisions, i.e. ”yes”, ”no”, and ”I do not know”, The last label occurs when input information is imprecise, incomplete or in general uncertain, and consequently, determining the unequivocal decision is impossible. We extend three-way decision (Hu et al., 2017; Liu et al., 2016; Sun et al., 2017; Yao, 2010; Yao, 2011) into four-way decision by extending possibilistic fuzzification to the three–dimensional possibility and necessity measures of fuzzy events.

Paper Citation

in Harvard Style

Nowicki R., Starczewski J. and Grycuk R. (2019). Extended Possibilistic Fuzzification for Classification. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: FCTA; ISBN 978-989-758-384-1, SciTePress, pages 343-350. DOI: 10.5220/0008168303430350

in Bibtex Style

@conference{fcta19,
author={Robert K. Nowicki and Janusz T. Starczewski and Rafał Grycuk},
title={Extended Possibilistic Fuzzification for Classification},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: FCTA},
year={2019},
pages={343-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008168303430350},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: FCTA
TI - Extended Possibilistic Fuzzification for Classification
SN - 978-989-758-384-1
AU - Nowicki R.
AU - Starczewski J.
AU - Grycuk R.
PY - 2019
SP - 343
EP - 350
DO - 10.5220/0008168303430350
PB - SciTePress