A weighted Cramér’s V Index for the assessment of stability in the fuzzy clustering of class C G protein-coupled receptors
Document typeConference report
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
After decades of intensive use, K-Means is still a common choice for crisp data clustering in real-world applications, particularly in biomedicine and bioinformatics. It is well-known that different initializations of the algorithm can lead to different solutions, precluding replicability. It has also been reported that even solutions with very similar errors may widely differ. A criterion for the choice of clustering solutions according to a combination of error and stability measures has recently been suggested. It is based on the use of Cramér’s V index, calculated from contingency tables, which is valid only for crisp clustering. Here, this criterion is extended to fuzzy and probabilistic clustering by first defining weighted contingency tables and a corresponding weighted Cramér’s V index. The proposed method is illustrated using Fuzzy C-Means in a proteomics problem.
CitationVellido, A., Halka, C., Nebot, M. A weighted Cramér’s V Index for the assessment of stability in the fuzzy clustering of class C G protein-coupled receptors. A: International Work-Conference on Bioinformatics and Biomedical Engineering. "Bioinformatics and Biomedical Engineering: Third International Conference, IWBBIO 2015, Granada, Spain, April 15-17, 2015: proceedings, part I (LNCS; 9043)". Granada: Springer, 2015, p. 536-547.