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In this paper we propose how a tree-structured self-organizing map (TS-SOM) can be used to impute incomplete data sets. The methodology has two parts, a new training algorithm utilizing incomplete data, and an imputation strategy that explains how the actual imputation is done. An introduction about evaluation studies of the proposed methodology is given(More)
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