Discovering patterns of missing data in survey databases: An application of rough sets

Authors:
Hai Wang;Shouhong Wang
Affiliations:
Sobey School of Business, Saint Mary's University, 903 Robie Street, Halifax, NS, Canada B3H 2W3;Charlton College of Business, University of Massachusetts Dartmouth, 285 Old Westport Road, Dartmouth, MA 02747-2300, USA
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Databases for data mining often have missing values. Missing data are often mistreated in data mining and valuable knowledge related to missing data is often overlooked. This study discusses patterns of missing data in survey databases. It proposes a framework of rough set rule induction method that enables the data miner to obtain association rules of patterns of missing data in a survey database. Through an experiment on a real-world data set, we demonstrate the approach to discovering knowledge about missing data.