A New Over-Sampling Method Based on Cluster Ensembles

@article{Chen2010ANO,
  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},
  year={2010},
  pages={599-604}
}
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

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 18 references

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

  • A. Asuncion, D. J. Newman
  • School of Information and Computer Science,
  • 2007
2 Excerpts

Similar Papers

Loading similar papers…