loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Francesco Cavrini 1 ; Lucia Rita Quitadamo 2 ; Luigi Bianchi 2 and Giovanni Saggio 2

Affiliations: 1 University of Rome “La Sapienza”, Italy ; 2 University of Rome “Tor Vergata”, Italy

ISBN: 978-989-758-053-6

Keyword(s): Brain-Computer Interface (BCI), Combination of Classifiers, Fuzzy Integral, Fuzzy Measure, Multi-Classifier Systems (MCS).

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

Abstract: In this paper we propose a framework for combination of classifiers using fuzzy measures and integrals that aims at providing researchers and practitioners with a simple and structured approach to deal with two issues that often arise in many pattern recognition applications: (i) the need for an automatic and user-specific selection of the best performing classifier or, better, ensemble of classifiers, out of the available ones; (ii) the need for uncertainty identification which should result in an abstention rather than an unreliable decision. We evaluate the framework within the context of Brain-Computer Interface, a field in which abstention and intersubject variability have a remarkable impact. Analysis of experimental data relative to five subjects shows that the proposed system is able to answer such needs.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.171.45.91

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Cavrini, F.; Quitadamo, L.; Bianchi, L. and Saggio, G. (2014). Combination of Classifiers using the Fuzzy Integral for Uncertainty Identification and Subject Specific Optimization - Application to Brain-Computer Interface.In Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014) ISBN 978-989-758-053-6, pages 14-24. DOI: 10.5220/0005035900140024

@conference{fcta14,
author={Francesco Cavrini. and Lucia Rita Quitadamo. and Luigi Bianchi. and Giovanni Saggio.},
title={Combination of Classifiers using the Fuzzy Integral for Uncertainty Identification and Subject Specific Optimization - Application to Brain-Computer Interface},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)},
year={2014},
pages={14-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005035900140024},
isbn={978-989-758-053-6},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)
TI - Combination of Classifiers using the Fuzzy Integral for Uncertainty Identification and Subject Specific Optimization - Application to Brain-Computer Interface
SN - 978-989-758-053-6
AU - Cavrini, F.
AU - Quitadamo, L.
AU - Bianchi, L.
AU - Saggio, G.
PY - 2014
SP - 14
EP - 24
DO - 10.5220/0005035900140024

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.