A Heuristic Approach for Cleaning Disguised Missing Data

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Provided by: International Journal for Technological Research in Engineering (IJTRE)
Topic: Data Management
Format: PDF
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially valid data values. Such missing values are known as disguised missing data, which may impair the quality of data analysis severely, such as causing significant biases and misleading results in hypothesis tests, correlation analysis and regressions. The very limited previous papers on cleaning disguised missing data use outlier mining and distribution anomaly detection.
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