Implementing Gene Expression Programming in the Parallel Environment for Big Datasets’ Classification
2019 ◽
Vol 06
(02)
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pp. 163-175
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Keyword(s):
The paper investigates a Gene Expression Programming (GEP)-based ensemble classifier constructed using the stacked generalization concept. The classifier has been implemented with a view to enable parallel processing with the use of Spark and SWIM — an open source genetic programming library. The classifier has been validated in computational experiments carried out on benchmark datasets. Also, it has been inbvestigated how the results are influenced by some settings. The paper is an extension of a previous paper of the authors.
Keyword(s):
2013 ◽
Vol 432
◽
pp. 565-570
2014 ◽
Vol 16
(1)
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pp. 83-91
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Keyword(s):
2014 ◽
Vol 2014
◽
pp. 1-16
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