In this paper, we present a missing data imputation method based on one of the most popular techniques in Knowledge Discovery in Databases (KDD), i.e. clustering technique. We comb...
Dan Li, Jitender S. Deogun, William Spaulding, Bil...
— Imputation of missing data is important in many areas, such as reducing non-response bias in surveys and maintaining medical documentation. Estimating the uncertainty inherent ...
Privacy Preserving Data Mining (PPDM) has become a popular topic in the research community. How to strike a balance between privacy protection and knowledge discovery in the shari...
Background: It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile ...
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...