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Books > Computing & IT > Applications of computing > Databases > Data mining
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Automating the Design of Data Mining Algorithms - An Evolutionary Computation Approach (Hardcover, 2010 ed.)
Loot Price: R2,662
Discovery Miles 26 620
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Automating the Design of Data Mining Algorithms - An Evolutionary Computation Approach (Hardcover, 2010 ed.)
Series: Natural Computing Series
Expected to ship within 18 - 22 working days
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Data mining is a very active research area with many successful
real-world app- cations. It consists of a set of concepts and
methods used to extract interesting or useful knowledge (or
patterns) from real-world datasets, providing valuable support for
decision making in industry, business, government, and science.
Although there are already many types of data mining algorithms
available in the literature, it is still dif cult for users to
choose the best possible data mining algorithm for their particular
data mining problem. In addition, data mining al- rithms have been
manually designed; therefore they incorporate human biases and
preferences. This book proposes a new approach to the design of
data mining algorithms. - stead of relying on the slow and ad hoc
process of manual algorithm design, this book proposes
systematically automating the design of data mining algorithms with
an evolutionary computation approach. More precisely, we propose a
genetic p- gramming system (a type of evolutionary computation
method that evolves c- puter programs) to automate the design of
rule induction algorithms, a type of cl- si cation method that
discovers a set of classi cation rules from data. We focus on
genetic programming in this book because it is the paradigmatic
type of machine learning method for automating the generation of
programs and because it has the advantage of performing a global
search in the space of candidate solutions (data mining algorithms
in our case), but in principle other types of search methods for
this task could be investigated in the future.
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