Advanced Symbolic Regression and Interpretable ML

Create a sophisticated symbolic regression framework capable of discovering interpretable mathematical models from complex datasets. Implement genetic programming techniques, sparse regression methods, and machine learning-guided model discovery. Develop a system supporting multiple complexity constraints, automated feature construction, and comprehensive model interpretability assessment. Include visualization of discovered symbolic expressions and uncertainty quantification.