Clustering stability and ground truth: numerical experiments

International Journal of Artificial Intelligence and Knowledge Discovery

Margarida G. M. S. Cardoso²  Maria José Amorim¹ 

[1] ISCTE-IUL

关键词: Clustering;    external validation;    stability;    indices of agreement;   

DOI  :  

学科分类：建筑学

来源: RG Education Society

【 摘 要 】

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) and to real data sets. 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

【 授权许可】

Unknown