Abstract
Stream data mining is an important data mining technique. Many stream data mining algorithms need only one pass to process data sets. More sophisticated state-of-the-art indexing techniques are needed to process, search, query the huge stream data. Ensemble stream data management technique is one of the stream data mining techniques. Ensemble-tree is an indexing data structure for storing classification rules of ensemble classifiers. Ensemble tree reduces time complexity of classifying a new stream record from linear to log. A new method is proposed for node splitting in the ensemble indexing tree construction. The new node splitting method is simple and easy to compute measures.
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