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Authors: Maria José Amorim 1 and Margarida Cardoso 2

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

ISBN: 978-989-758-158-8

Keyword(s): Clustering, External Validation, Stability.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Stability has been considered an important property for evaluating clustering solutions. Nevertheless, there are no conclusive studies on the relationship between this property and the capacity to recover clusters inherent to data (“ground truth”). This study focuses on this relationship resorting to synthetic data generated under diverse scenarios (controlling relevant factors). Stability is evaluated using a weighted cross-validation procedure. Indices of agreement (corrected for agreement by chance) are used both to assess stability and external validation. The results obtained reveal a new perspective so far not mentioned in the literature. Despite the clear relationship between stability and external validity when a broad range of scenarios is considered, within-scenarios conclusions deserve our special attention: faced with a specific clustering problem (as we do in practice), there is no significant relationship between stability and the ability to recover data cluster s. (More)

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Paper citation in several formats:
Amorim, M. and Cardoso, M. (2015). Clustering Stability and Ground Truth: Numerical Experiments.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 259-264. DOI: 10.5220/0005597702590264

@conference{kdir15,
author={Maria José Amorim. and Margarida Cardoso.},
title={Clustering Stability and Ground Truth: Numerical Experiments},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={259-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005597702590264},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Clustering Stability and Ground Truth: Numerical Experiments
SN - 978-989-758-158-8
AU - Amorim, M.
AU - Cardoso, M.
PY - 2015
SP - 259
EP - 264
DO - 10.5220/0005597702590264

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