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Authors: Maria José Amorim 1 and Margarida G. M. S. Cardoso 2

Affiliations: 1 ISEL and Inst. Univ. de Lisboa (ISCTE-IUL), Portugal ; 2 ISCTE Busines School-IUL, Portugal

Keyword(s): Adjusted Indices, Indices of Paired Agreement, Clustering Evaluation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: In the present paper we focus on the performance of clustering algorithms using indices of paired agreement to measure the accordance between clusters and an a priori known structure. We specifically propose a method to correct all indices considered for agreement by chance – the adjusted indices are meant to provide a realistic measure of clustering performance. The proposed method enables the correction of virtually any index – overcoming previous limitations known in the literature - and provides very precise results. We use simulated datasets under diverse scenarios and discuss the pertinence of our proposal which is particularly relevant when poorly separated clusters are considered. Finally we compare the performance of EM and K-Means algorithms, within each of the simulated scenarios and generally conclude that EM generally yields best results.

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Paper citation in several formats:
Amorim, M. and G. M. S. Cardoso, M. (2014). Paired Indices for Clustering Evaluation - Correction for Agreement by Chance. In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 3: ICEIS; ISBN 978-989-758-027-7; ISSN 2184-4992, SciTePress, pages 164-170. DOI: 10.5220/0004868301640170

@conference{iceis14,
author={Maria José Amorim. and Margarida {G. M. S. Cardoso}.},
title={Paired Indices for Clustering Evaluation - Correction for Agreement by Chance},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 3: ICEIS},
year={2014},
pages={164-170},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004868301640170},
isbn={978-989-758-027-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 3: ICEIS
TI - Paired Indices for Clustering Evaluation - Correction for Agreement by Chance
SN - 978-989-758-027-7
IS - 2184-4992
AU - Amorim, M.
AU - G. M. S. Cardoso, M.
PY - 2014
SP - 164
EP - 170
DO - 10.5220/0004868301640170
PB - SciTePress

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