Fuzzy C-means

Fuzzy C-means is a clustering algorithm used to group data points based on their similarities. Unlike traditional methods that assign each point to a single group, fuzzy c-means allows points to belong to multiple clusters with different degrees of membership. This approach recognizes that data points can be somewhat related to multiple groups, providing a nuanced understanding of the data structure. It iteratively updates the cluster centers and the membership levels until it finds the best fit, making it useful for complex, overlapping data patterns where clear-cut divisions aren't ideal.