Online Neuro Fuzzy Clustering of Data with Omissions and Outliers based on Сompletion Strategy
Yevgeniy V. Bodyanskiy, Аліна Шафроненко, Diana Rudenko · 2019
In the paper new recurrent adaptive algorithms for fuzzy clustering of data with missing values are proposed.This algorithm is based on fuzzy clustering procedures and self-learning Kohonen's rule using principle "Winner-Takes-More" with Cauchy neighborhood function.Using proposed approach it's possible to solve clustering task in on-line mode in situation when the amount of missing values in data is too big.