C-means clustering

C-means clustering is a method used to group a set of data points into clusters based on their similarities. Each cluster is defined by a center point, and data points are assigned to the nearest center based on a calculated distance. Unlike traditional clustering, where each point belongs to only one cluster, C-means allows points to belong to multiple clusters to varying degrees. This flexibility makes it useful for complex datasets, as it can capture overlapping patterns and provide insights into the underlying structure of the data.