MATLAB Implementation of Fuzzy C-Means (FCM) Algorithm with GUI

This implementation utilizes MATLAB to execute the Fuzzy C-Means (FCM) clustering algorithm. The algorithm incorporates a user-friendly graphical interface that simplifies the clustering process, enabling users to efficiently perform data segmentation and pattern recognition operations. Key implementation features include customizable clustering parameters (number of clusters, fuzziness exponent), interactive data visualization tools, and real-time convergence monitoring through MATLAB's plotting capabilities. The core algorithm employs iterative optimization of cluster centroids and membership matrices using Euclidean distance calculations, with built-in validation for handling multidimensional datasets. This makes the algorithm particularly effective for processing complex data structures while maintaining computational accuracy. The implementation serves as a practical tool applicable across various domains including image segmentation, bioinformatics, and market segmentation analysis.