Missing Data in Distributed Analysis Sample Clauses

Missing Data in Distributed Analysis. The above-mentioned techniques of distributed analysis assume that the data are com- plete. However, it is especially common that data from multiple sources are subject to missing values. Based on our knowledge, Xxxxxxxxxxx and Xxxxxx (2008) is the first and only paper that investigated missing data in a distributed analysis. In that paper, the author propose a privacy-preserving single imputation algorithm based on decision trees. The method can deal with the missing data problem when the data are collected from two sources and observed to have a univariate missing-data pattern.
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