Missing Data Imputation for Categorical Variables
Dealing with missing data is a crucial part of everyday data analysis. The IMIC algorithm is a missing data imputation method that can handle mixed numerical and categorical datasets. However, the categorical data are crucial for this work. This paper proposes the new improvement of the IMIC algorit...
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| Hlavní autoři: | , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Czech Statistical Office
2022-09-01
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| Edice: | Statistika: Statistics and Economy Journal |
| Témata: | |
| On-line přístup: | https://www.czso.cz/documents/10180/167607763/32019722q3_249-260_hornicek_analyses.pdf/23e277ec-e001-4036-9809-ceda5dda950d?version=1.1 |
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