A Cluster Based MARDL Algorithm for Drifting Categorical Data

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Provided by: International Journal of Modern Engineering Research (IJMER)
Topic: Data Management
Format: PDF
Clustering is an important problem in data mining. Most of the earlier work on clustering focused on numeric attributes which have a natural ordering on their attribute values. Recently, clustering data with categorical attributes, whose attribute values do not have a natural ordering, has received some attention. However, previous algorithms do not give a formal description of the clusters they discover and some of them assume that the user post-processes the output of the algorithm to identify the final clusters.
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