Огляд методу глибокої нечіткої кластеризації даних

Abstract

Deep fuzzy clustering is one of the directions in the development of fuzzy clustering methods. This approach combines the advantages of fuzzy logic and deep learning for efficient data separation and analysis. The main idea is to use a deep neural network to represent data in a new feature space that takes into account the complex relationships between features and helps preserve the structural features of the data. Deep fuzzy clustering can solve the problems associated with matching high-dimensional and fuzzy data, which are often encountered in real-world problems.