symbolic-regression

Automatically discover mathematical expressions that best fit your data using genetic programming with e-graph optimization. (by DataHaskell)

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  • Dataframe 1.0.0.0
    1 project | news.ycombinator.com | 23 Mar 2026
    Author here. At the time I worked in fraud detection and we needed to automate file generation for our BRMS. Initially created this to experiment with “models as dataframe expressions” and Haskell is great for DSL-like stuff. That work is still on going: https://github.com/DataHaskell/symbolic-regression and dataframe has a native sparse oblique tree implementation.

    As it’s grown it’s been pretty cool to have transparent schema transformations instead of every function mapping a statement a dataframe you can have function signatures like:

    ```

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2 months ago

DataHaskell/symbolic-regression is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of symbolic-regression is Haskell.


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