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Authors: José M. Cadenas ; M. Carmen Garrido and Raquel Martínez

Affiliation: University of Murcia, Spain

ISBN: 978-989-8425-83-6

Keyword(s): Fuzzy partition, Imperfect information, Fuzzy random forest ensemble, Imprecise data.

Related Ontology Subjects/Areas/Topics: Approximate Reasoning and Fuzzy Inference ; Artificial Intelligence ; Computational Intelligence ; Fuzzy Systems ; Pattern Recognition: Fuzzy Clustering and Classifiers ; Soft Computing

Abstract: Classification is an important task in Data Mining. In order to carry out classification, many classifiers require a previous preparatory step for their data. In this paper we focus on the process of discretization of attributes because this process is a very important part in Data Mining. In many situations, the values of the attributes present imprecision because imperfect information inevitably appears in real situations for a variety of reasons. Although, many efforts have been made to incorporate imperfect data into classification techniques, there are still many limitations as to the type of data, uncertainty and imprecision that can be handled. Therefore, in this paper we propose an algorithm to construct fuzzy partitions from imprecise information and we evaluate them in a Fuzzy Random Forest ensemble which is able to work with imprecise information too. Also, we compare our proposal with results of other works.

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Paper citation in several formats:
M. Cadenas J., Carmen Garrido M. and Martínez R. (2011). CONSTRUCTING FUZZY PARTITIONS FROM IMPRECISE DATA.In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011) ISBN 978-989-8425-83-6, pages 379-388. DOI: 10.5220/0003644303790388

@conference{fcta11,
author={José M. Cadenas and M. Carmen Garrido and Raquel Martínez},
title={CONSTRUCTING FUZZY PARTITIONS FROM IMPRECISE DATA},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011)},
year={2011},
pages={379-388},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003644303790388},
isbn={978-989-8425-83-6},
}

TY - CONF

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2011)
TI - CONSTRUCTING FUZZY PARTITIONS FROM IMPRECISE DATA
SN - 978-989-8425-83-6
AU - M. Cadenas J.
AU - Carmen Garrido M.
AU - Martínez R.
PY - 2011
SP - 379
EP - 388
DO - 10.5220/0003644303790388

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