A New Classification Algorithm for Data Stream

Автор: Li Su, Hong-yan Liu, Zhen-Hui Song

Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs

Статья в выпуске: 4 vol.3, 2011 года.

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Associative classification (AC) which is based on association rules has shown great promise over many other classification techniques on static dataset. Meanwhile, a new challenge have been proposed in that the increasing prominence of data streams arising in a wide range of advanced application. This paper describes and evaluates a new associative classification algorithm for data streams AC-DS, which is based on the estimation mechanism of the Lossy Counting (LC) and landmark window model. And AC-DS was applied to mining several datasets obtained from the UCI Machine Learning Repository and the result show that the algorithm is effective and efficient.

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Data streams, associative classification, frequent itemsets

Короткий адрес: https://sciup.org/15010242

IDR: 15010242

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