A formal algorithm for verifying the validity of clustering results based on model checking.

Autor: Shaobin Huang, Yuan Cheng, Dapeng Lang, Ronghua Chi, Guofeng Liu
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Zdroj: PLoS ONE, Vol 9, Iss 3, p e90109 (2014)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0090109
Popis: The limitations in general methods to evaluate clustering will remain difficult to overcome if verifying the clustering validity continues to be based on clustering results and evaluation index values. This study focuses on a clustering process to analyze crisp clustering validity. First, we define the properties that must be satisfied by valid clustering processes and model clustering processes based on program graphs and transition systems. We then recast the analysis of clustering validity as the problem of verifying whether the model of clustering processes satisfies the specified properties with model checking. That is, we try to build a bridge between clustering and model checking. Experiments on several datasets indicate the effectiveness and suitability of our algorithms. Compared with traditional evaluation indices, our formal method can not only indicate whether the clustering results are valid but, in the case the results are invalid, can also detect the objects that have led to the invalidity.
Databáze: Directory of Open Access Journals