Abstract
We present an algorithm to impute missingvalues from given dataalone, and analyse its performance. Theproposed procedure is based onnon-numeric rule based data analysis, and aimsto maximise consistency of imputation from known values. Incontrast to the prevailingstatistical imputation algorithms, it does notmake representationalassumptions or presupposes other modelconstraints. Therefore, it is suitablefor a wide variety of data – sets, and can beused as a pre-processing step beforeresorting to harder numerical methods.
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Gediga, G., Düntsch, I. Maximum Consistency of Incomplete Data via Non-Invasive Imputation. Artificial Intelligence Review 19, 93–107 (2003). https://doi.org/10.1023/A:1022188514489
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DOI: https://doi.org/10.1023/A:1022188514489