Robust Random Forest-Based All-Relevant Feature Ranks for Trustworthy AI.

^*Corresponding author for this work

Research output: Contribution to journal › Research letter

Original language	English
Journal	Studies in Health Technology and Informatics
DOIs	https://doi.org/10.3233/SHTI220418
Publication status	Published - 2022

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This output contributes to the following UN Sustainable Development Goals (SDGs)

@article{e78099cecb174bb7a4b56ca4f95733a9,

title = "Robust Random Forest-Based All-Relevant Feature Ranks for Trustworthy AI.",

author = "Bastian Pfeifer and Andreas Holzinger and Michael Schimek",

year = "2022",

doi = "10.3233/SHTI220418",

language = "English",

journal = "Studies in Health Technology and Informatics",

issn = "0926-9630",

publisher = "IOS Press BV",

}

TY - JOUR

T1 - Robust Random Forest-Based All-Relevant Feature Ranks for Trustworthy AI.

AU - Holzinger, Andreas

A2 - Pfeifer, Bastian

A2 - Schimek, Michael

PY - 2022

Y1 - 2022

UR - https://pubmed.ncbi.nlm.nih.gov/35612038

U2 - 10.3233/SHTI220418

DO - 10.3233/SHTI220418

M3 - Research letter

C2 - 35612038

SN - 0926-9630

JO - Studies in Health Technology and Informatics

JF - Studies in Health Technology and Informatics

ER -