A Memetic Algorithm for Symbolic Regression

Sun, Haoyuan; Moscato, Pablo

doi:10.1109/cec.2019.8789889

Cited by 16 publications

(20 citation statements)

References 19 publications

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“…While our memetic algorithm does individual search optimization with a modified Nelder-Mead algorithm (Fajfar et al, 2016), the nature of the nonlinear optimization problem indicates that more powerful solvers could later be used. We have chosen to start with a Nelder-Mead solver as a way of ensuring and promoting reproducibility, keeping the core memetic algorithm as simple as possible (Sun & Moscato, 2019) for this first in-depth test of performance of the new representation in real-world problems.…”

Section: Individual Model Optimization Via a Direct Search Methodsmentioning

confidence: 99%

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Moscato

Sun

Haque

2021

Expert Systems with Applications

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Individual Model Optimization Via a Direct Search Methodsmentioning

confidence: 99%

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Moscato

Sun

Haque

2021

Expert Systems with Applications

Self Cite

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“…While our memetic algorithm does individual search optimization with a modified Nelder-Mead algorithm [61], the nature of the non-linear optimization problem indicates that more powerful solvers could later be used. We have chosen to start with a Nelder-Mead solver as a way of ensuring and promoting reproducibility, keeping the core memetic algorithm as simple as possible [63] for this first in-depth test of performance of the new representation in real-world problems.…”

Section: Individual Model Optimization Via a Direct Search Methodsmentioning

confidence: 99%

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Moscato,

Sun,

Haque

2020

Preprint

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We present an approach for regression problems that employs analytic continued fractions as a novel representation. Comparative computational results using a memetic algorithm are reported in this work. Our experiments included fifteen other different machine learning approaches including five genetic programming methods for symbolic regression and ten machine learning methods. The comparison on training and test generalization was performed using 94 datasets of the Penn State Machine Learning Benchmark. The statistical tests showed that the generalization results using analytic continued fractions provides a powerful and interesting new alternative in the quest for compact and interpretable mathematical models for artificial intelligence.

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“…In 2019, a regression approach based on 'Continued Fraction' (CFR) was proposed; it views multivariate regression as a non-linear optimization problem and the authors used a memetic algorithm to find approximations to the unknown target functions from experimental data [30]. Memetic algorithms are a population-based approach to solve computational problems that are posed as optimization tasks and have been heavily used for other data analytics in combinatorial optimization problems [31,32,33] and that are also showing impressive results for non-linear regression problems [34,30,35,36] and other machine learning problems [37].…”

Section: Continued Fraction Regressionmentioning

confidence: 99%

“…We can use the same idea to approximate a function f (x) by replacing each a i and b i with other functions of x. [30] proposed that we can approximate the "target function" of a multivariate regression problem, given a set of examples, and that it can be expressed as a multivariate function f : R n → R of the form:…”

Section: Continued Fraction Regressionmentioning

confidence: 99%

Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays

Moscato,

Craig,

Egan

et al. 2021

Preprint

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The date of the first performance of a play of Shakespeare's time must usually be guessed with reference to multiple indirect external sources, or to some aspect of the content or style of the play. Identifying these dates is important to literary history and to accounts of developing authorial styles, such as Shakespeare's. In this study, we took a set of Shakespeare-era plays (181 plays from the period 1585-1610), added the best-guess dates for them from a standard reference work as metadata, and calculated a set of probabilities of individual words in these samples. We applied 11 regression methods to predict the dates of the plays at an 80/20 training/test split. We withdrew one play at a time, used the best-guess date metadata with the probabilities and weightings to infer its date, and thus built a model of date-probabilities interaction. We introduced a memetic algorithm-based Continued Fraction Regression (CFR) which delivered models using a small number of variables, leading to an interpretable model and reduced dimensionality. An in-depth analysis of the most commonly occurring 20 words in the CFR models in 100 independent runs helps explain the trends in linguistic and stylistic terms. The analysis with the subset of words revealed an interesting correlation of signature words with the Shakespeare-era play's genre.Keywords Shakespeare-era plays • continued fraction regression • dating of plays • play's genre • Memetic Algorithm

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A Memetic Algorithm for Symbolic Regression

Cited by 16 publications

References 19 publications

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays

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