Phimmarin Keerin1, Tossapon Boongoen2,*
CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4009-4025, 2022, DOI:10.32604/cmc.2022.020261
Abstract The problem of missing values has long been studied by researchers working in areas of data science and bioinformatics, especially the analysis of gene expression data that facilitates an early detection of cancer. Many attempts show improvements made by excluding samples with missing information from the analysis process, while others have tried to fill the gaps with possible values. While the former is simple, the latter safeguards information loss. For that, a neighbour-based (KNN) approach has proven more effective than other global estimators. The paper extends this further by introducing a new summarization method to the KNN model. It is… More >
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