Rockett, P.I. orcid.org/0000-0002-4636-7727 (2018) Pruning of Genetic Programming Trees Using Permutation Tests. Technical Report.
Abstract
We present a novel approach based on statistical permutation tests for pruning redundant subtrees from genetic programming (GP) trees. We observe that over a range of regression problems, median tree sizes are reduced by around 20% largely independent of test function, and that while some large subtrees are removed, the median pruned subtree comprises just three nodes; most take the form of an exact algebraic simplification. Our statistically-based pruning technique has allowed us to explore the hypothesis that a given subtree can be replaced with a constant if this substitution results in no statistical change to the behaviour of the parent tree—what we term approximate simplification. In the eventuality, we infer that &95% of the pruned subtrees are the result of algebraic simplifications, which provides some practical insight into the scope of removing redundancies in GP trees.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 The Author(s). For reuse permissions, please contact the Author(s). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Sep 2018 15:43 |
Last Modified: | 06 Sep 2018 09:04 |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:134313 |