Developing New Fitness Functions in Genetic Programming for Classification With Unbalanced Data
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gp-bibliography.bib Revision:1.8010
- @Article{Bhowan:2012:SMC,
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author = "Urvesh Bhowan and Mark Johnston and Mengjie Zhang",
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title = "Developing New Fitness Functions in Genetic
Programming for Classification With Unbalanced Data",
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journal = "IEEE Transactions on Systems, Man, and Cybernetics,
Part B: Cybernetics",
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year = "2012",
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month = apr,
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volume = "42",
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number = "2",
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pages = "406--421",
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size = "16 pages",
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abstract = "Machine learning algorithms such as genetic
programming (GP) can evolve biased classifiers when
data sets are unbalanced. Data sets are unbalanced when
at least one class is represented by only a small
number of training examples (called the minority class)
while other classes make up the majority. In this
scenario, classifiers can have good accuracy on the
majority class but very poor accuracy on the minority
class(es) due to the influence that the larger majority
class has on traditional training criteria in the
fitness function. This paper aims to both highlight the
limitations of the current GP approaches in this area
and develop several new fitness functions for binary
classification with unbalanced data. Using a range of
real-world classification problems with class
imbalance, we empirically show that these new fitness
functions evolve classifiers with good performance on
both the minority and majority classes. Our approaches
use the original unbalanced training data in the GP
learning process, without the need to artificially
balance the training examples from the two classes
(e.g., via sampling).",
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keywords = "genetic algorithms, genetic programming, GP learning
process, biased classifiers, binary classification,
class imbalance, data sets, fitness functions, machine
learning algorithms, majority class, minority class,
training criteria, unbalanced data, unbalanced training
data, data handling, learning (artificial
intelligence), pattern classification",
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DOI = "doi:10.1109/TSMCB.2011.2167144",
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ISSN = "1083-4419",
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notes = "Also known as \cite{6029340}",
- }
Genetic Programming entries for
Urvesh Bhowan
Mark Johnston
Mengjie Zhang
Citations