Fuzzy C Means

Fuzzy C-Means (FCM) is a popular clustering technique that extends traditional clustering methods by allowing data points to belong to multiple clusters with varying degrees of membership. Unlike hard clustering, where each data point is assigned to a single cluster, FCM assigns a probability value between 0 and 1 to each data point for every cluster. This approach is particularly effective for datasets with overlapping clusters, as it captures the inherent uncertainty and ambiguity in data. FCM is widely used in various applications, including image processing, pattern recognition, and document clustering, enabling more nuanced data analysis and interpretation.