LSROM: Learning Self-Refined Organizing Map for Fast Imbalanced Streaming Data Clustering

arXiv:2404.09243v1 Announce Type: new
Abstract: Streaming data clustering is a popular research topic in the fields of data mining and machine learning. Compared to static data, streaming data, which is usually analyzed in data chunks, is more susceptible to encountering the dynamic cluster imbalanced issue. That is, the imbalanced degree of clusters varies in different streaming data chunks, leading to corruption in either the accuracy or the efficiency of streaming data analysis based on existing clustering methods. Therefore, we propose …

abstract arxiv cluster clustering cs.lg cs.ne data data mining dynamic fields issue machine machine learning map mining popular research streaming streaming data type