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Authors: Francesco Campobasso and Annarita Fanizzi

Affiliation: University of Bari, Italy

Keyword(s): Fuzzy Discriminant Analysis, Non Linear Regression Models, Iterative Fuzzy k-Means Method, Entrepreneurial Propensity.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Fuzzy Systems ; Mathematical Foundations: Fuzzy Set Theory and Fuzzy Logic ; Pattern Recognition: Fuzzy Clustering and Classifiers ; Soft Computing

Abstract: The common classification techniques are designed for a rigid (even if probabilistic) allocation of each unit into one of several groups. Nevertheless the dissimilarity among combined units often leads to consider the opportunity of assigning each of them to more than a single group with different degrees of membership. In previous works we proposed a fuzzy approach to discriminant analysis, structured by linearly regressing the degrees of membership of each unit to every groups on the same variables used in a preliminary clustering. In this work we show that non-linear regression models can be used more profitably than linear ones. The applicative case concerns the entrepreneurial propensity of provinces in Central and Southern Italy, even if our methodological proposal was initially conceived to assign new customers to defined groups for Customer Relationship Management (CRM) purposes.

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Paper citation in several formats:
Campobasso, F. and Fanizzi, A. (2013). A Fuzzy Approach to Discriminant Analysis based on the Results of an Iterative Fuzzy k-Means Method. In Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 257-264. DOI: 10.5220/0004553802570264

@conference{fcta13,
author={Francesco Campobasso. and Annarita Fanizzi.},
title={A Fuzzy Approach to Discriminant Analysis based on the Results of an Iterative Fuzzy k-Means Method},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA},
year={2013},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004553802570264},
isbn={978-989-8565-77-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA
TI - A Fuzzy Approach to Discriminant Analysis based on the Results of an Iterative Fuzzy k-Means Method
SN - 978-989-8565-77-8
IS - 2184-3236
AU - Campobasso, F.
AU - Fanizzi, A.
PY - 2013
SP - 257
EP - 264
DO - 10.5220/0004553802570264
PB - SciTePress

- Science and Technology Publications, Lda.
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