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Books > Computing & IT > Applications of computing > Artificial intelligence
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Stream Data Mining: Algorithms and Their Probabilistic Properties (Hardcover, 1st ed. 2020)
Loot Price: R5,033
Discovery Miles 50 330
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Stream Data Mining: Algorithms and Their Probabilistic Properties (Hardcover, 1st ed. 2020)
Series: Studies in Big Data, 56
Expected to ship within 12 - 17 working days
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This book presents a unique approach to stream data mining. Unlike
the vast majority of previous approaches, which are largely based
on heuristics, it highlights methods and algorithms that are
mathematically justified. First, it describes how to adapt static
decision trees to accommodate data streams; in this regard, new
splitting criteria are developed to guarantee that they are
asymptotically equivalent to the classical batch tree. Moreover,
new decision trees are designed, leading to the original concept of
hybrid trees. In turn, nonparametric techniques based on Parzen
kernels and orthogonal series are employed to address concept drift
in the problem of non-stationary regressions and classification in
a time-varying environment. Lastly, an extremely challenging
problem that involves designing ensembles and automatically
choosing their sizes is described and solved. Given its scope, the
book is intended for a professional audience of researchers and
practitioners who deal with stream data, e.g. in telecommunication,
banking, and sensor networks.
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