Uncertainty in Data Mining

Ayad Tareq Imam; Rafid Qahtan Allawi

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Paper

Uncertainty in Data Mining

In Proceedings of the 1st International Conference on Computing and Emerging Sciences ICCES - Volume 1, 74-78, 2020 , Erbil, Iraq

Authors: Ayad Tareq Imam ¹ and Rafid Qahtan Allawi ²

Affiliations: ¹ Faculty of IT, Isra University, Amman 11622, Jordan ; ² The Higher Institute of Health, Anbar, Iraq

Keyword(s): Data Mining, Uncertainty, Fuzzy Set, Artificial Neural Network, Neuro-Fuzzy, Relative-Fuzzy.

Abstract: This paper aims to articulate the current approaches to handle the uncertainty problem in data mining (DM). The difficulties in DM are given to show the impact of the uncertainty problem in DM’s various applications. As it has been stated that is no common DM method to handle the uncertainty problem in DM and based upon the literature of cognitive science, this paper highlights a new classification approach to overcome the uncertainty problem in DM that is the Relative-Fuzzy (RF) approach and its ML/RFL-Based Net software tool.

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Paper citation in several formats:

Imam, A. and Allawi, R. (2021). Uncertainty in Data Mining. In Proceedings of the 1st International Conference on Computing and Emerging Sciences - ICCES; ISBN 978-989-758-497-8, SciTePress, pages 74-78. DOI: 10.5220/0010461400740078

@conference{icces21,
author={Ayad Tareq Imam. and Rafid Qahtan Allawi.},
title={Uncertainty in Data Mining},
booktitle={Proceedings of the 1st International Conference on Computing and Emerging Sciences - ICCES},
year={2021},
pages={74-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010461400740078},
isbn={978-989-758-497-8},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Computing and Emerging Sciences - ICCES
TI - Uncertainty in Data Mining
SN - 978-989-758-497-8
AU - Imam, A.
AU - Allawi, R.
PY - 2021
SP - 74
EP - 78
DO - 10.5220/0010461400740078
PB - SciTePress