Comparing Fitness Functions for Genetic Feature Transformation
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- @Article{Klusacek:2016:IFAC-PapersOnLine,
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author = "Jan Klusacek and Vaclav Jirsik",
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title = "Comparing Fitness Functions for Genetic Feature
Transformation",
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journal = "IFAC-PapersOnLine",
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volume = "49",
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number = "25",
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pages = "299--304",
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year = "2016",
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note = "14th \{IFAC\} Conference on Programmable Devices and
Embedded Systems \{PDES\} 2016Brno, Czech Republic, 5-7
October 2016",
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ISSN = "2405-8963",
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DOI = "doi:10.1016/j.ifacol.2016.12.053",
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URL = "http://www.sciencedirect.com/science/article/pii/S2405896316326891",
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abstract = "Abstract: A representation of features is a very
important parameter when creating machine learning
models. The main goal of this paper is to introduce a
way to compare feature space transformations that
change this representation. It particularly deals with
a comparison of a method that uses a genetic
programming based on different fitness functions for
transformation of feature space. The fitness function
is a very important part of the genetic algorithm
because it defines required properties of new feature
space. Several possible fitness functions are described
and compared in this paper. The process of the
comparison is also introduced in this paper and
selected functions are tested and their results are
compared to each other. These results are compared and
upsides and downsides of each method are discussed in
conclusion. A part of the work is a framework used to
automate processes needed to create this comparison.",
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keywords = "genetic algorithms, genetic programming, Feature
space, Feature space transformation, Fitness function,
Machine learning",
- }
Genetic Programming entries for
Jan Klusacek
Vaclav Jirsik
Citations