Cluster-Based Algorithms for Dealing with Missing Values

@inproceedings{Fujikawa2002ClusterBasedAF,
  title={Cluster-Based Algorithms for Dealing with Missing Values},
  author={Yoshikazu Fujikawa and Tu Bao Ho},
  booktitle={PAKDD},
  year={2002}
}
We first survey existing methods to deal with missing values and report the results of an experimental comparative evaluation in terms of their processing cost and quality of imputing missing values. We then propose three cluster-based mean-and-mode algorithms to impute missing values. Experimental results show that these algorithms with linear complexity can achieve comparative quality as sophisticated algorithms and therefore are applicable to large datasets. 

From This Paper

Topics from this paper.
17 Citations
9 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Probabilistic induction by dynamic path generation in virtual trees

  • A. P. White
  • Research and Development in Expert Systems III
  • 1987

Probabilistic induction by dynamic path generation in virtual trees. In Research and Development in Expert Systems III, edited by M.A

  • A. P. White
  • 1987
1 Excerpt

Experiments in automatic learning of medical diagnostic rules

  • I. Kononenko, I. Bratko, E. Roskar
  • Technical Report. Jozef Stefan Institute,
  • 1984

Similar Papers

Loading similar papers…