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README.md
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# Eureqa.jl
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Symbolic regression built on Julia, and interfaced by Python.
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Uses regularized evolution and simulated annealing
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## Installation
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# Eureqa.jl
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**Symbolic regression built on Julia, and interfaced by Python.
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Uses regularized evolution and simulated annealing.**
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Backstory: we used the original
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[eureqa](https://www.creativemachineslab.com/eureqa.html)
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in our [paper](https://arxiv.org/abs/2006.11287) to
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convert a graph neural network into
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an analytic equation describing dark matter overdensity. However,
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eureqa is GUI-only, doesn't allow for user-defined
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operators, has no distributed capabilities,
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and has become proprietary. Thus, the goal
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of this package is to have an open-source symbolic regression tool
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as efficient as eureqa, while also exposing a configurable
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python interface.
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The algorithms here implement regularized evolution, as in
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[AutoML-Zero](https://arxiv.org/abs/2003.03384),
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but with additional algorithmic changes such as simulated
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annealing, and classical optimization of constants.
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## Installation
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