Crossmark

Enhancing trust and interpretability of complex machine learning models using local interpretable model agnostic shap explanations

Published Online: 2023-10-25

Published Print: 2024-10

Authors

Parisineni, Sai Ram Aditya

Pal, Mayukha
License Information

Text and Data Mining valid from 2023-10-25

Version of Record valid from 2023-10-25
More Information

Article History

Received: 8 April 2023

Accepted: 11 September 2023

First Online: 25 October 2023

Declarations

:

: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The data obtained for our analysis are from the available public domain database made for academic research purposes.

Document is current