Divisive clustering of high dimensional data streams
نویسندگان
چکیده
منابع مشابه
Divisive clustering of high dimensional data streams
Clustering streaming data is gaining importance as automatic data acquisition technologies are deployed in diverse applications. We propose a fully incremental projected divisive clustering method for high-dimensional data streams that is motivated by high density clustering. The method is capable of identifying clusters in arbitrary subspaces, estimating the number of clusters, and detecting c...
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The data stream problem has been studied extensively in recent years, because of the great ease in collection of stream data. The nature of stream data makes it essential to use algorithms which require only one pass over the data. Recently, single-scan, stream analysis methods have been proposed in this context. However, a lot of stream data is highdimensional in nature. High-dimensional data ...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2015
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-015-9597-y