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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
22 Knowledge Discovery from Data Streams
Step 3
s
3
= ((24 + 11)/4)/2, d
3
= {((24 11)/4)/2}
s
3
= 4.375, d
3
= {1.625}
The sequence {4.375, 1.625, 2.5, 2.75, 1.5, .5, 1.5, 1} are the coefficients
of the expansion. The process consists of adding/subtracting pairs of numbers,
divided by the normalization factor.
Wavelet analysis is popular in several streaming applications, because most
signals can be represented using a small set of coefficients. Matias et al. (1998)
present an efficient algorithm based on multi-resolution wavelet decomposition
for building histograms with application to database problems, like selectivity
estimation. In the same research
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Publisher Resources

ISBN: 9781439826126