A New Over-Sampling Method Based on Cluster Ensembles

  title={A New Over-Sampling Method Based on Cluster Ensembles},
  author={Si Chen and Gongde Guo and Lifei Chen},
  journal={2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops},
Most of the traditional classification methods behave undesirable, particularly producing poor predictive accuracy for the minority class of the imbalanced data from real world applications. This paper proposes a novel over-sampling strategy to handle imbalanced data based on cluster ensembles, named CE-SMOTE, which aims to provide a better training platform by introducing clustering consistency index to find out the cluster boundary minority samples and then over-sampling these minority… CONTINUE READING


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UCI machine learning repository [http://www.ics.uci.edu/~mlearn/MLRepositor-y.html], Irvine, CA: University of California

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