Introduction - If you have any usage issues, please Google them yourself
Clustering analysis is one of the important research contents in data mining. The clustering criteria are summarized. The research status and progress of five traditional clustering algorithms are summarized comprehensively. Some new clustering algorithms are used. By combing, according to the sample attribution relationship, sample data preprocessing, sample similarity measure, sample update strategy, sample high-dimensionality and fusion with other disciplines, nearly 20 new algorithms in clustering, Such as granular clustering, uncertain clustering, quantum clustering, nuclear clustering, spectral clustering, clustering integration, concept clustering, spherical shell clustering, affine clustering, data stream clustering, etc., respectively Generalization.