Fuzzy–rough Fuzzification in General FL Classifiers

Janusz T. Starczewski, Robert K. Nowicki, Katarzyna Nieszporek

2019

Abstract

In this paper, a three-dimensional version of fuzzy-rough fuzzification is examined for classification tasks. Similar approach based on interval fuzzy-rough fuzzification has been demonstrated to classify with three decision labels of confidence, one of which were uncertain. The method proposed here relies on the use of fuzzification of inputs with a triangular membership function describing the nature of imprecision in data. As a result, we implement in fuzzy classifiers three dimensional membership functions using the calculus of general type-2 fuzzy sets. The approach is justified when more confidence labels are expected from the decision system, especially when the classifier is embedded in a recurrent hierarchical decision system working on easily available economic, extended, and advanced expensive real data.

Paper Citation

in Harvard Style

Starczewski J., Nowicki R. and Nieszporek K. (2019). Fuzzy–rough Fuzzification in General FL Classifiers. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: FCTA; ISBN 978-989-758-384-1, SciTePress, pages 335-342. DOI: 10.5220/0008168103350342

in Bibtex Style

@conference{fcta19,
author={Janusz T. Starczewski and Robert K. Nowicki and Katarzyna Nieszporek},
title={Fuzzy–rough Fuzzification in General FL Classifiers},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: FCTA},
year={2019},
pages={335-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008168103350342},
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 - Fuzzy–rough Fuzzification in General FL Classifiers
SN - 978-989-758-384-1
AU - Starczewski J.
AU - Nowicki R.
AU - Nieszporek K.
PY - 2019
SP - 335
EP - 342
DO - 10.5220/0008168103350342
PB - SciTePress