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Knowledge Discovery from Data Streams
book

Knowledge Discovery from Data Streams

by Joao Gama
May 2010
Intermediate to advanced content levelIntermediate to advanced
255 pages
8h 11m
English
Chapman and Hall/CRC
Content preview from Knowledge Discovery from Data Streams
84 Knowledge Discovery from Data Streams
Figure 6.1: The Clustering Feature Tree in BIRCH. B is the maximum number
of CFs in a level of the tree.
the CF-tree, where each node is a tuple (Clustering Feature) that contains
the sufficient statistics describing a set of data points, and compresses all in-
formation of the CFs below in the tree. BIRCH only works with continuous
attributes. It was designed for very large datasets, explicitly taking into ac-
count time and memory constraints. For example, not all data points are used
for clustering, dense regions of data points are treated as sub-clusters. BIRCH
might scan data twice to refine the CF-tree, although ...
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Publisher Resources

ISBN: 9781439826126