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Evolutionary Decision Trees in Large-Scale Data Mining (Paperback, 1st ed. 2019)
Loot Price: R3,684
Discovery Miles 36 840
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Evolutionary Decision Trees in Large-Scale Data Mining (Paperback, 1st ed. 2019)
Series: Studies in Big Data, 59
Expected to ship within 10 - 15 working days
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This book presents a unified framework, based on specialized
evolutionary algorithms, for the global induction of various types
of classification and regression trees from data. The resulting
univariate or oblique trees are significantly smaller than those
produced by standard top-down methods, an aspect that is critical
for the interpretation of mined patterns by domain analysts. The
approach presented here is extremely flexible and can easily be
adapted to specific data mining applications, e.g. cost-sensitive
model trees for financial data or multi-test trees for gene
expression data. The global induction can be efficiently applied to
large-scale data without the need for extraordinary resources. With
a simple GPU-based acceleration, datasets composed of millions of
instances can be mined in minutes. In the event that the size of
the datasets makes the fastest memory computing impossible, the
Spark-based implementation on computer clusters, which offers
impressive fault tolerance and scalability potential, can be
applied.
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