articleIEEE Transactions on Neural Networks and Learning SystemsMay 20, 2025Closed access

Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering

YZYiqun ZhangSFSen FengPWPengkai WangZTZexi TanXLXiaopeng Luo

Guangdong University of Technology · Hong Kong Baptist University

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Abstract

Streaming data clustering is a popular research topic in data mining and machine learning. Since streaming data is usually analyzed in data chunks, it is more susceptible to encountering the dynamic cluster imbalance issue. That is, the imbalance ratio (IR) of clusters changes over time, which can easily lead to fluctuations in either the accuracy or the efficiency of streaming data clustering. Therefore, an accurate and efficient streaming data clustering approach is proposed to adapt to the drifting and imbalanced cluster distributions. We first design a self-growth map (SGM) that can automatically arrange neurons on demand according to local distribution, and thus achieve fast and incremental adaptation to…

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49
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Topics & keywords

Topics
Keywords
  • Cluster analysis
  • Computer science
  • Streaming data
  • Artificial intelligence
  • Data mining
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