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Authors: F. Jorge F. Duarte 1 ; João M. M. Duarte 1 ; M. Fátima C. Rodrigues 1 and Ana L. N. Fred 2

Affiliations: 1 Instituto Superior de Engenharia do Porto, Portugal ; 2 Instituto Superior Técnico, Portugal

ISBN: 978-989-674-011-5

Keyword(s): Cluster ensemble selection, Cluster ensembles, Data clustering, Unsupervised learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Clustering and Classification Methods ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: In order to combine multiple data partitions into a more robust data partition, several approaches to produce the cluster ensemble and various consensus functions have been proposed. This range of possibilities in the multiple data partitions combination raises a new problem: which of the existing approaches, to produce the cluster ensembles’ data partitions and to combine these partitions, best fits a given data set. In this paper, we address the cluster ensemble selection problem. We proposed a new measure to select the best consensus data partition, among a variety of consensus partitions, based on a notion of average cluster consistency between each data partition that belongs to the cluster ensemble and a given consensus partition. We compared the proposed measure with other measures for cluster ensemble selection, using 9 different data sets, and the experimental results shown that the consensus partitions selected by our approach usually were of better quality in comparison wit h the consensus partitions selected by other measures used in our experiments. (More)

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Paper citation in several formats:
Jorge F. Duarte F.; M. M. Duarte J.; Fátima C. Rodrigues M.; L. N. Fred A. and (2009). CLUSTER ENSEMBLE SELECTION - Using Average Cluster Consistency.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009) ISBN 978-989-674-011-5, pages 85-95. DOI: 10.5220/0002308500850095

@conference{kdir09,
author={F. {Jorge F. Duarte} and João {M. M. Duarte} and M. {Fátima C. Rodrigues} and Ana {L. N. Fred}},
title={CLUSTER ENSEMBLE SELECTION - Using Average Cluster Consistency},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)},
year={2009},
pages={85-95},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002308500850095},
isbn={978-989-674-011-5},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)
TI - CLUSTER ENSEMBLE SELECTION - Using Average Cluster Consistency
SN - 978-989-674-011-5
AU - Jorge F. Duarte, F.
AU - M. M. Duarte, J.
AU - Fátima C. Rodrigues, M.
AU - L. N. Fred, A.
PY - 2009
SP - 85
EP - 95
DO - 10.5220/0002308500850095

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