Feature Selection and Classification Using Ensembles of Genetic Programs and Within-class and Between-class Permutations
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Ivert:2015:CEC,
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author = "Annica Ivert and Claus Aranha and Hitoshi Iba",
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title = "Feature Selection and Classification Using Ensembles
of Genetic Programs and Within-class and Between-class
Permutations",
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booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary
Computation (CEC 2015)",
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year = "2015",
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editor = "Yadahiko Murata",
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pages = "1121--1128",
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address = "Sendai, Japan",
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month = "25-28 " # may,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4799-7491-7",
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DOI = "doi:10.1109/CEC.2015.7257015",
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abstract = "Many feature selection methods are based on the
assumption that important features are highly
correlated with their corresponding classes, but mainly
uncorrelated with each other. Often, this assumption
can help eliminate redundancies and produce good
predictors using only a small subset of features.
However, when the predictability depends on
interactions between features, such methods will fail
to produce satisfactory results. In this paper a method
that can find important features, both independently
and dependently discriminative, is introduced. This
method works by performing two different types of
permutation tests that classify each of the features as
either irrelevant, independently predictive or
dependently predictive. It was evaluated using a
classifier based on an ensemble of genetic programs.
The attributes chosen by the permutation tests were
shown to yield classifiers at least as good as the ones
obtained when all attributes were used during training
- and often better. The proposed method also fared well
when compared to other attribute selection methods such
as RELIEFF and CFS. Furthermore, the ability to
determine whether an attribute was independently or
dependently predictive was confirmed using artificial
datasets with known dependencies.",
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notes = "1005 hrs 15256 CEC2015",
- }
Genetic Programming entries for
Annica Ivert
Claus de Castro Aranha
Hitoshi Iba
Citations