Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs
author
Medianovskyi, Kyrylo
Malakauskas, Aidas
Lakstutiene, Ausrine
Ben Yahia, Sadok
statement of authorship
Kyrylo Medianovskyi, Aidas Malakauskas, Ausrine Lakstutiene, Sadok Ben Yahia
source
Procedia computer science
publisher
Elsevier
journal volume number month
vol. 225
year of publication
2023
pages
p. 2163-2172 : ill
conference name, date
27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023, 6-8 September 2023
conference location
Athens, Greece
url
https://doi.org/10.1016/j.procs.2023.10.207
subject term
tehisintellekt
tehisõpe
keyword
CATE
double ML
explainable artificial intelligence
interpretable machine learning
Partial dependence plot
SHAP
ISSN
1877-0509
notes
Bibliogr.: 38 ref
The special issue 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023, Athens, 6 September 2023 - 8 September 2023
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
Scopus
https://www.scopus.com/sourceid/19700182801
https://www.scopus.com/record/display.uri?eid=2-s2.0-85183562382&origin=inward&txGid=61f1a8644f69e7798996dacd9baf1fbe
category (general)
Computer science
Arvutiteadus
category (sub)
Computer science. General computer science
Arvutiteadus. Üldine arvutiteadus
quartile
Q2
TalTech department
tarkvarateaduse instituut
language
inglise