Gaining Deeper Insights in Symbolic Regression

@inproceedings{Affenzeller2013GainingDI,
  title={Gaining Deeper Insights in Symbolic Regression},
  author={Michael Affenzeller and Stephan M. Winkler and Gabriel Kronberger and Michael Kommenda and Bogdan Burlacu and Stefan Wagner},
  booktitle={GPTP},
  year={2013}
}
A distinguishing feature of symbolic regression using genetic programming is its ability to identify complex nonlinear white-box models. This is especially relevant in practice where models are extensively scrutinized in order to gain knowledge about underlying processes. This potential is often diluted by the ambiguity and complexity of the models produced by genetic programming. In this contribution we discuss several analysis methods with the common goal to enable better insights in the… CONTINUE READING

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