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Advisor(s)
Abstract(s)
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 clusters.
Description
Keywords
Clustering External validation Stability
Citation
AMORIM, Maria José; CARDOSO, Margarida G. M. S. – Clustering stability and ground truth: numerical experiments. In 2015 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K). Lisbon, Portugal: IEEE, 2015. ISBN 978-1-5090-1967-0. Pp. 259-264
Publisher
Institute of Electrical and Electronics Engineers