Data Mining Based on Condensed Hierarchical Clustering Algorithm

  • Zengjun BiEmail author
  • Yaoquan Han
  • Caiquan Huang
  • Min Wang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1060)


Clustering is an important part of data mining, which aims to divide unknown sample data into multiple classes according to similarity relationship. According to the characteristics of multi-subject high-dimension of training data, this paper preprocesses the training data by linear dimensionality reduction and analyzes the training data based on condensed hierarchical clustering algorithm. From the perspective of practical application, this clustering analysis method of training data effectively differentiates personnel reasonably and intuitively reflects the performance characteristics of various types of personnel, providing scientific guidance for the development and implementation of training plans.


Data mining Hierarchical clustering Training data 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Zengjun Bi
    • 1
    Email author
  • Yaoquan Han
    • 1
  • Caiquan Huang
    • 1
  • Min Wang
    • 1
  1. 1.Air Force Early Warning AcademyWuhanChina

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