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Aliyu Sani Sambo_PhD Thesis_Final Version_Submitted Jan 2022_Final Award Apr 2022.pdf
Preview of Download (7MB)
🔗 Source: open-access.bcu.ac.uk
📊 Size: 7.14 MB
👤 Author: Aliyu Sani Sambo 15142485
⬇️ Downloads: 112

Summary

This thesis proposes using evaluation time to produce simple machine learning models with genetic programming (GP), addressing the issue of evolving solutions growing unnecessarily complex. Two approaches are used to discourage complexity: explicitly penalizing models with long evaluation times and implicitly discouraging long evaluation times by incorporating a race condition in the GP process. The proposed methods yield accurate yet simple solutions, improving runtime and training speed, and effectively manage functional complexity in various GP applications, including regression models, feature engineering, robot control, and Boolean logic problems.

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Description

This thesis proposes using evaluation time to produce simple machine learning models with genetic programming (GP), addressing the issue of evolving solutions...

Technical Information

  • File Format: PDF
  • File Size: 7.14 MB
  • Pages: 313
  • Language: EN
  • Author: Aliyu Sani Sambo 15142485
  • Total Downloads: 112
  • Last Updated: 1 month ago

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