Online Сredibilistic Fuzzy Clustering of Data with Gaps - Bodyanskiy, Ye. V.; Shafronenko, A. Yu.; Klymova, I. N. (My University, 2020)
The problem of online fuzzy clustering based on credibilistic approaches based on the partial distance strategy and processing of data with gaps was proposed. The considered methods are simple in numerical implementation, being essentially gradient procedures for optimizing objective functions of a special type.
Keywords: Fuzzy clustering; data with gaps