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ELI5

ELI5: A library for debugging/inspecting machine learning classifiers and explaining their predictions.

Keywords for this software

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  • interpretability
  • open source
  • eXplainable Artificial Intelligence
  • arXiv_publication
  • taxonomy
  • R packages
  • Machine Learning
  • XAI
  • R
  • arXiv_stat.ML
  • transparency
  • explainability
  • arXiv_cs.LG

  • URL: eli5.readthedocs.io/en...
  • Code
  • InternetArchive
  • Authors: M. Korobov; K. Lopuhin
  • Dependencies: Python

  • Add information on this software.


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References in zbMATH (referenced in 2 articles )

Showing results 1 to 2 of 2.
y Sorted by year (citations)

  1. Arya, Vijay; Bellamy, Rachel K. E.; Chen, Pin-Yu; Dhurandhar, Amit; Hind, Michael; Hoffman, Samuel C.; Houde, Stephanie; Liao, Q. Vera; Luss, Ronny; Mojsilović, Aleksandra; Mourad, Sami; Pedemonte, Pablo; Raghavendra, Ramya; Richards, John T.; Sattigeri, Prasanna; Shanmugam, Karthikeyan; Singh, Moninder; Varshney, Kush R.; Wei, Dennis; Zhang, Yunfeng: AI Explainability 360: an extensible toolkit for understanding data and machine learning models (2020)
  2. Szymon Maksymiuk, Alicja Gosiewska, Przemyslaw Biecek: Landscape of R packages for eXplainable Artificial Intelligence (2020) arXiv

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      • 68 Computer science

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