Volltext-Downloads (blau) und Frontdoor-Views (grau)

Interpreting Black-box Machine Learning Models for High Dimensional Datasets

Export metadata

Additional Services

Search Google Scholar Check availability

Statistics

Show usage statistics
Metadaten
Document Type:Conference Object
Language:English
Author:Md. Rezaul Karim, Md Shajalal, Alexander Graß, Till Döhmen, Sisay Adugna Chala, Alexander Boden, Christian Beecks, Stefan Decker
Parent Title (English):2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), 09-13 October 2023, Thessaloniki, Greece
Number of pages:10
First Page:1
Last Page:10
ISBN:979-8-3503-4503-2
DOI:https://doi.org/10.1109/DSAA60987.2023.10302562
Publisher:IEEE
Date of first publication:2023/11/06
Copyright:©2023 IEEE
Funding:This paper is a collaborative effort and based on the PhD thesis [17] by the first author and the second author’s work as part of the Marie Sktodowska-Curie project funded by the Horizon Europe 2020 research and innovation program of the European Union under the grant agreement no. 955422.
Keyword:Attention mechanism; Black-box models; Curse of dimensionality; Interpretability; Model surrogation
Departments, institutes and facilities:Fachbereich Wirtschaftswissenschaften
Institut für Verbraucherinformatik (IVI)
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 005 Computerprogrammierung, Programme, Daten
Entry in this database:2023/11/13