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We propose an interactive visual analytics tool that is applied for the combined analysis of multidimensional numerical and categorical data. The tool helps the analyst not only to find the clusters of similar objects but also to identify the important features specific to these clusters. The efficacy of the various functionalities of the tool is examined analyzing epidemiological data to understand the pathogenesis of obstructive sleep apnea. Our approach helps the user to visually analyze the data and get a better understanding of the data. 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