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Title:
Hierarchical cluster analysis for partially synthetic data generation
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Creator:
Levon H. Aslanyan ; Vardan H. Topchyan
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Uncontrolled Keywords:
Ասլանյան Լ. ; Թոփչյան Վ. ; Асланян Л. ; Топчян В.
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Abstract:
Limiting the risk of information disclosure is now common for statistical agencies. One of the widespread approaches is to release the synthetic, public use of microdata sets. To put it another way, thanks to the multiple imputations the sensitive variables of original data are replaced by new/synthetic values. This paper introduces the method for partially synthetic data generation based on hierarchical cluster analysis.