C-means algorithm

C-means is a clustering algorithm used to group similar data points into clusters. Unlike traditional methods that assign each data point to a single cluster, C-means allows data points to belong to multiple clusters with varying degrees of membership. It works by iteratively updating the cluster centers and the membership levels until convergence. This method is useful in fields such as image processing and pattern recognition, as it can better capture complex structures within data, making it a powerful tool for analysis and decision-making in various applications.