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arxiv: 1803.06226 · v2 · pith:TI53G3ADnew · submitted 2018-03-13 · 💻 cs.MS · cs.NE· math.OC· physics.data-an

Glyph: Symbolic Regression Tools

classification 💻 cs.MS cs.NEmath.OCphysics.data-an
keywords glyphregressionsymbolicexperimentsgeneticgithubinterfacenumerical
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We present Glyph - a Python package for genetic programming based symbolic regression. Glyph is designed for usage let by numerical simulations let by real world experiments. For experimentalists, glyph-remote provides a separation of tasks: a ZeroMQ interface splits the genetic programming optimization task from the evaluation of an experimental (or numerical) run. Glyph can be accessed at http://github.com/ambrosys/glyph . Domain experts are be able to employ symbolic regression in their experiments with ease, even if they are not expert programmers. The reuse potential is kept high by a generic interface design. Glyph is available on PyPI and Github.

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