Detecting disguised missing data

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2009
Belen, Rahime
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In some applications, explicit codes are provided for missing data such as NA (not available) however many applications do not provide such explicit codes and valid or invalid data codes are recorded as legitimate data values. Such missing values are known as disguised missing data. Disguised missing data may affect the quality of data analysis negatively, for example the results of discovered association rules in KDD-Cup-98 data sets have clearly shown the need of applying data quality management prior to analysis. In this thesis, to tackle the problem of disguised missing data, we analyzed embedded unbiased sample heuristic (EUSH), demonstrated the methods drawbacks and proposed a new methodology based on Chi Square Two Sample Test. The proposed method does not require any domain background knowledge and compares favorably with EUSH.
Information systems, Data analysis.
http://etd.lib.metu.edu.tr/upload/12610411/index.pdf
https://hdl.handle.net/11511/18492
Graduate School of Informatics, Thesis

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Citation Formats
R. Belen, “Detecting disguised missing data,” M.S. - Master of Science, Middle East Technical University, 2009.
METU IIS - Integrated Information Service open@metu.edu.tr