Title :
An analysis of robustness of partition coefficient index
Author_Institution :
Dept. of Inf. Manage., Kun Shan Univ., Tainan
Abstract :
We know that the partition coefficient index has the monotonic tendency with cluster number c. Moreover, they always select the smallest cluster number c=2 as a optimal cluster number estimate when data contains some noise points. In this paper, we will discuss this problem by defining the validity measure of each single data point. We then define the singular point that has equal memberships to each cluster. By analyzing the influence of the singular point on the validity index, we can then give some guidelines for designing the fuzzy c-partitions based validity indexes that can avoid the influence of the noise.
Keywords :
fuzzy set theory; pattern clustering; fuzzy c-partitions; fuzzy clustering algorithm; monotonic tendency; partition coefficient index; single data point; validity indexes; Clustering algorithms; Data structures; Entropy; Guidelines; Noise robustness; Partitioning algorithms; Principal component analysis; Scattering;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630393