Clustering with Fuzzy C-means and Common Challenges
Songyin Deng · Journal of Physics Conference Series · 2020
Abstract Clustering algorithm is massively used in various fields such as computer vision and so do FCM. One of the purpose of this paper is to generate new insight into improvement on general clustering algorithms through this inspection of one specific clustering algorithm (FCM) help. Three common challenges of clustering (Noise problem, long operational time, and initial bias) in Fuzzy C-Means algorithm and corresponding solutions to each of these problems are introduced. Further potential of meta learning and adversarial learning to solve the clustering problems are recognized in the end.