How to Measure Explainability and Interpretability of Machine Learning Results

Created by W.Langdon from gp-bibliography.bib Revision:1.8311

@InProceedings{Winkler:2024:GPTP,

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

}

Genetic Programming entries for Elisabeth Mayrhuber Bogdan Burlacu Stephan M Winkler

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