paper-with-me

홈 › Papers

Interaction-Transformation Evolutionary Algorithm for Symbolic Regression

2019-02-11 · Fabricio Olivetti de Franca, Guilherme Seidyo Imai Aldeia

The Interaction-Transformation (IT) is a new representation for Symbolic Regression that restricts the search space into simpler, but expressive, function forms. This representation has the advantage of creating a smoother search space unlike the space generated by Expression Trees, the common representation used in Genetic Programming. This paper introduces an Evolutionary Algorithm capable of evolving a population of IT expressions supported only by the mutation operator. The results show that this representation is capable of finding better approximations to real-world data sets when compared to traditional approaches and a state-of-the-art Genetic Programming algorithm.

📄 PDF Abstract BibTeX arXiv:1902.03983

Code (1)

folivetti/ITEA 공식 구현

Tasks

regressionSymbolic Regression

Similar Papers 제목 키워드 기반

Alleviating Overfitting in Transformation-Interaction-Rational Symbolic Regression with Multi-Objective Optimization

2025-01-03 · Fabricio Olivetti de Franca

The Transformation-Interaction-Rational is a representation for symbolic regression that limits the search space of functions to the ratio of two nonlinear functions each one defined as the linear regression of transform…

regressionSymbolic Regression

Binary and Multinomial Classification through Evolutionary Symbolic Regression

2022-06-25 · Moshe Sipper

We present three evolutionary symbolic regression-based classification algorithms for binary and multinomial datasets: GPLearnClf, CartesianClf, and ClaSyCo. Tested over 162 datasets and compared to three state-of-the-ar…

ClassificationregressionSymbolic Regression

LLM-Meta-SR: Learning to Evolve Selection Operators for Symbolic Regression

2025-05-24 · Hengzhe Zhang, Qi Chen, Bing Xue, Mengjie Zhang

Large language models (LLMs) have revolutionized algorithm development, yet their application in symbolic regression, where algorithms automatically discover symbolic expressions from data, remains constrained and is typ…

regressionSymbolic Regression

Shape-constrained Symbolic Regression -- Improving Extrapolation with Prior Knowledge

2021-03-29 · Gabriel Kronberger, Fabricio Olivetti de França, Bogdan Burlacu, Christian Haider 외

We investigate the addition of constraints on the function image and its derivatives for the incorporation of prior knowledge in symbolic regression. The approach is called shape-constrained symbolic regression and allow…

Evolutionary AlgorithmsregressionSymbolic Regression

Efficient Generator of Mathematical Expressions for Symbolic Regression

2023-02-20 · Sebastian Mežnar, Sašo Džeroski, Ljupčo Todorovski

We propose an approach to symbolic regression based on a novel variational autoencoder for generating hierarchical structures, HVAE. It combines simple atomic units with shared weights to recursively encode and decode th…

Evolutionary AlgorithmsregressionSymbolic Regression