Lightweight Symbolic Regression with the Interaction-Transformation Representation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Aldeia:2018:CEC,
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author = "Guilherme Aldeia and Fabricio {de Franca}",
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title = "Lightweight Symbolic Regression with the
Interaction-Transformation Representation",
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booktitle = "2018 IEEE Congress on Evolutionary Computation (CEC)",
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year = "2018",
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editor = "Marley Vellasco",
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address = "Rio de Janeiro, Brazil",
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month = "8-13 " # jul,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CEC.2018.8477951",
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abstract = "Symbolic Regression techniques stand out from other
regression analysis tools because of the possibility of
generating powerful but yet simple expressions. These
simple expressions may be useful in many practical
situations in which the practitioner wants to interpret
the obtained results, fine tune the model, or
understand the generating phenomena. Despite this
possibility, the current state-of-the-art algorithms
for Symbolic Regression usually require a high
computational budget while having little guarantees
regarding the simplicity of the returned expressions.
Recently, a new Data Structure representation for
mathematical expressions, called
Interaction-Transformation (IT), was introduced
together with a search-based algorithm named SymTree
that surpassed a subset of the recent Symbolic
Regression algorithms and even some state-of-the-art
nonlinear regression algorithms, while returning simple
expressions as a result. This paper introduces a
lightweight tool based on this algorithm, named Lab
Assistant. This tool runs on the client-side of any
compatible Internet browser with JavaScript. Alongside
this tool, two algorithms using the IT representation
are introduced. Some experiments are performed in order
to show the potential of the Lab Assistant to help
practitioners, professors, researchers and students
willing to experiment with Symbolic Regression. The
results showed that this tool is competent to find the
correct expression for many well known Physics and
Engineering relations within a reasonable average time
frame of a few seconds. This tool opens up lots of
possibilities in Symbolic Regression research for
low-cost devices to be used in applications where a
high-end computer is not available.",
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notes = "WCCI2018",
- }
Genetic Programming entries for
Guilherme Seidyo Imai Aldeia
Fabricio Olivetti de Franca
Citations