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Computer Science > Neural and Evolutionary Computing

Title: TurboGP: A flexible and advanced python based GP library

Abstract: We introduce TurboGP, a Genetic Programming (GP) library fully written in Python and specifically designed for machine learning tasks. TurboGP implements modern features not available in other GP implementations, such as island and cellular population schemes, different types of genetic operations (migration, protected crossovers), online learning, among other features. TurboGP's most distinctive characteristic is its native support for different types of GP nodes to allow different abstraction levels, this makes TurboGP particularly useful for processing a wide variety of data sources.
Subjects: Neural and Evolutionary Computing (cs.NE); Machine Learning (cs.LG)
Cite as: arXiv:2309.00149 [cs.NE]
  (or arXiv:2309.00149v1 [cs.NE] for this version)

Submission history

From: Lino Rodriguez-Coayahuitl PhD [view email]
[v1] Thu, 31 Aug 2023 21:50:23 GMT (129kb,D)

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