K-Medoid Clustering Shows Negative Impact In Missing Data Imputation

Abstract

Missing Data Imputation imputes the missing values from the known values. Rather than imputing from the whole dataset, imputation techniques are applied in the clusters generated by using clustering algorithm. In this paper, K-Medoid clustering is used. But when compared the results in terms of accuracy, it seems that K-Medoid clusters are not suited for Missing Data Imputation.

Authors and Affiliations

R Malarvizhi, Dr. Antony Selvadoss Thanamani

Keywords

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  • EP ID EP27534
  • DOI -
  • Views 392
  • Downloads 7

How To Cite

R Malarvizhi, Dr. Antony Selvadoss Thanamani (2013). K-Medoid Clustering Shows Negative Impact In Missing Data Imputation. International Journal of Research in Computer and Communication Technology, 2(1), -. https://europub.co.uk/articles/-A-27534