NRMCS : Noise removing based on the MCS

  title={NRMCS : Noise removing based on the MCS},
  author={Xizhao Wang and Bo Wu and Yu-Lin He and Xiang-Hao Pei},
  journal={2008 International Conference on Machine Learning and Cybernetics},
MCS (minimal consistent set) is one of the classical algorithms for minimal consistent subset selection problem. However, when noisy samples are present classification accuracy can suffer. In addition, noise affect the size of minimal consistent set. Therefore, removing noise is an important issue before sample selection. In this paper, an improvement approach based on MCS to select the representative samples is proposed. Compared with other algorithms which remove the noise by Wilson editing… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.
6 Citations
16 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 16 references

Dasarathy.Minimal consistent set (MCS) identification for optimal nearest neighbor decision systems design [J

  • B V.
  • IEEE. Trans Cybern. March
  • 1994
Highly Influential
3 Excerpts

Remembering to forget

  • Smyth, M.T.B.andKeane
  • Proceedings of the Fourteenth International…
  • 1995
3 Excerpts

Similar Papers

Loading similar papers…