An adjustable p-exponential clustering algorithm
Valmir Macário Filho, Francisco de A.T. de Carvalho · The European Symposium on Artificial Neural Networks · 2014
This paper proposes a new exponential clustering algorithm (XPFCM) by reformulating the clustering objective function with an additional parameter p to adjust the exponential behavior for membership assignment. The clustering exper- iments show that the proposed method assign data to the clusters better than other fuzzy C-means (FCM) variants.