How to Measure Explainability and Interpretability of Machine Learning Results
Created by W.Langdon from
gp-bibliography.bib Revision:1.8276
- @InProceedings{Winkler:2024:GPTP,
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author = "Elisabeth Mayrhuber and Bogdan Burlacu and
Stephan M. Winkler",
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title = "How to Measure Explainability and Interpretability of
Machine Learning Results",
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booktitle = "Genetic Programming Theory and Practice XXI",
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year = "2024",
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editor = "Stephan M. Winkler and Wolfgang Banzhaf and
Ting Hu and Alexander Lalejini",
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series = "Genetic and Evolutionary Computation",
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pages = "357--374",
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address = "University of Michigan, USA",
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month = jun # " 6-8",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, XAI",
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isbn13 = "978-981-96-0076-2",
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URL = "
https://heal.heuristiclab.com/news/post/gptp-xxi",
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DOI = "
doi:10.1007/978-981-96-0077-9_18",
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notes = "Published in 2025 after the workshop",
- }
Genetic Programming entries for
Elisabeth Mayrhuber
Bogdan Burlacu
Stephan M Winkler
Citations