MDL and BIC most reliably select low test-error models and recover ground-truth expressions in symbolic regression benchmarks.
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spotoptim is an open-source Python package that implements a Kriging-based optimization loop with Expected Improvement, mixed-variable support, noise handling via OCBA, parallelization, and restart mechanisms for black-box optimization.
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A Comparative Study of Model Selection Criteria for Symbolic Regression
MDL and BIC most reliably select low test-error models and recover ground-truth expressions in symbolic regression benchmarks.
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Optimization with SpotOptim
spotoptim is an open-source Python package that implements a Kriging-based optimization loop with Expected Improvement, mixed-variable support, noise handling via OCBA, parallelization, and restart mechanisms for black-box optimization.