A data mining approach to assessing the extent of damage of missing values in survey
by Hai Wang, Shouhong Wang
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 2, No. 3, 2007

Abstract: Survey data are often incomplete. Incomplete data are often mistreated and damages of missing values in survey are often overlooked in data mining. This study proposes a classification-based data mining approach to assessing the extent of damage of missing values in survey. Using this approach, an incomplete observation is translated into fuzzy observations. These fuzzy observations are used to test the classifier that has been trained by the complete data set of the survey. The test results provide a base for discovering knowledge about the implication of missing data and the quality of the survey.

Online publication date: Fri, 19-Oct-2007

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