Improving the flexibility of shape-constrained symbolic regression with extended constraints

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Shape Constraints in Symbolic Regression using Penalized Least Squares

V Martinek, J Reuter, O Frotscher, S Mostaghim… - arxiv preprint arxiv …, 2024 - arxiv.org
We study the addition of shape constraints (SC) and their consideration during the
parameter identification step of symbolic regression (SR). SC serve as a means to introduce …
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Multi-Representation Genetic Programming: A Case Study on Tree-based and Linear Representations

Z Huang, Y Mei, F Zhang, M Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Existing genetic programming (GP) methods are typically designed based on a certain
representation, such as tree-based or linear representations. These representations show …
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Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation

C Haider, FO de Franca, B Burlacu, F Bachinger… - … Theory and Practice XX, 2024 - Springer
We present different approaches for including knowledge in data-based modeling. For this,
we utilize the model representation of symbolic regression (SR), which represents the …
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