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cs.LG2025
Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models
Nathan Haut, Zenas Huang, Adam Alessio
Choosing models from a well-fitted evolved population that generalizes beyond training data is difficult. We introduce a pragmatic method to estimate model complexity using Hessian…
cs.LG2022
Active Learning Improves Performance on Symbolic RegressionTasks in StackGP
Nathan Haut, Wolfgang Banzhaf, Bill Punch
In this paper we introduce an active learning method for symbolic regression using StackGP. The approach begins with a small number of data points for StackGP to model. To improve…