On Kernel Based Rough Intuitionistic Fuzzy C-means Algorithm and a Comparative Analysis

摘要: Clustering of real life data for analysis has gained popularity and imprecise methods or their hybrid approaches attracted many researchers late. Recently, rough intuitionistic fuzzy c-means algorithm was introduced studied by Tripathy et al [3] it found to be superior all other algorithms in this family. Kernel based counter part these have been behave better than corresponding Euclidean distance algorithms. Very recently kernel put forth Bhargav [4]. A comparative over standard datasets images established the superiority its algorithm. In paper we introduce show that is sequel; i.e. both normal We establish through experimental taking different type inputs using accuracy measures.