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Frequent set mining is a well researched problem due to its application in many areas of data mining such as clustering, classification and association rule mining. Most of the existing work focuses on categorical and batch data and do not scale well for large datasets. In this work, we focus on frequent set mining for mixed data. We introduce a discretization methodology to find meaningful bin boundaries...
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