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.
Data streams, associative classification, frequent itemsets
Короткий адрес: https://sciup.org/15010242
IDR: 15010242
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