Instance Selection for Geometric Semantic Genetic Programming
Created by W.Langdon from
gpbibliography.bib Revision:1.7175
 @InProceedings{Miranda:2020:CEC,

author = "Luis Fernando Miranda and Luiz Otavio Oliveira and
Joao Francisco Martins and Gisele Pappa",

title = "Instance Selection for Geometric Semantic Genetic
Programming",

booktitle = "2020 IEEE Congress on Evolutionary Computation, CEC
2020",

year = "2020",

editor = "Yaochu Jin",

pages = "paper id24548",

address = "internet",

month = "1924 " # jul,

organization = "IEEE Computational Intelligence Society",

publisher = "IEEE Press",

keywords = "genetic algorithms, genetic programming: Poster",

isbn13 = "9781728169293",

DOI = "doi:10.1109/CEC48606.2020.9185867",

abstract = "Geometric Semantic Genetic Programming (GSGP) is a
method that exploits the geometric properties
describing the spatial relationship between possible
solutions to a problem in an ndimensional semantic
space. In symbolic regression problems, n is equal to
the number of training instances. Although very
effective, the GSGP semantic space can become
excessively big in most real applications, where the
value of n is high, having a negative impact on the
effectiveness of the GSGP search process. This paper
tackles this problem by reducing the dimensionality of
GSGP semantic space in symbolic regression problems
using instance selection methods. Our approach relies
on weighting functionsto estimate the relative
importance of each instance based on its position with
respect to its nearest neighboursand on dimensionality
reduction techniquesto improve the notion of closeness
between instances, generating datasets with simplified
input spaces. Experiments were performed on a set of 15
datasets and our experimental analysis shows that using
instance selection by instance weighting and
dimensionality reduction does improve the effectiveness
of the search with almost no impact on root mean square
error results.",

notes = "https://wcci2020.org/
Federal University of Minas Gerais, Brazil.
Also known as \cite{9185867}",
 }
Genetic Programming entries for
Luis Fernando Miranda
Luiz Otavio Oliveira
Joao Francisco Martins
Gisele L Pappa
Citations