FCM, GG, GK Algorithms with Clustering Validity Measures

This article presents comprehensive MATLAB source code implementations for three prominent fuzzy clustering algorithms: FCM (Fuzzy C-Means), GG (Gustafson-Kessel), and GK (Gustafson-Kessel variant). The codebase includes specialized functions for calculating three essential cluster validity indices - Partition Coefficient (PC), Partition Entropy (PE), and Xie-Beni (XB) index - which help evaluate clustering quality and determine optimal cluster numbers. Each algorithm implementation features proper initialization methods, iterative optimization processes, and convergence criteria handling. The accompanying documentation provides detailed explanations of each algorithm's mathematical foundation, parameter configuration guidelines, and practical usage examples. Through studying these implementations and documentation, developers can gain deeper insights into fuzzy clustering mechanics, validity assessment techniques, and real-world application scenarios for pattern recognition and data mining tasks.