Abstract

In this study we analyze behavior of two types of coefficients for determining the suitable number of clusters obtained when fuzzy cluster analysis is applied. First one is Dunn's coefficient which contains membership degrees in its computational formula; second one is the average silhouette width, used primarily for evaluating hard clustering. There have already been attempts to compare different coefficients for determining the clustering quality or number of clusters respectively. Unfortunately coefficients for evaluating hard clustering and for fuzzy clustering were studied separately only. We tested coefficients efficiency when clustering both data set consisting of generated objects with the known number of clusters and real data sets with unknown number of clusters. The analysis showed the limitations of these two coefficients especially for the cases when clusters are really fuzzy.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.