Inproceedings,
Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models.
A. Qadi, M. Trocan, T. Frossard, and N. Rodríguez.MEDES, page 115-122. ACM, (2022)
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- BibTeX key
- conf/medes/QadiTFR22
- entry type
- inproceedings
- booktitle
- MEDES
- year
- 2022
- pages
- 115-122
- publisher
- ACM
- crossref
- conf/medes/2022
- ee
- https://doi.org/10.1145/3508397.3564835
- isbn
- 978-1-4503-9219-8
- url
- http://dblp.uni-trier.de/db/conf/medes/medes2022.html#QadiTFR22
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- please select -%0 Conference Paper
%1 conf/medes/QadiTFR22
%A Qadi, Ayoub El
%A Trocan, Maria
%A Frossard, Thomas
%A Rodríguez, Natalia Díaz
%B MEDES
%D 2022
%E Damiani, Ernesto
%E Silvestri, Claudio
%E Ivanovic, Mirjana
%E Chbeir, Richard
%E Manolopoulos, Yannis
%I ACM
%K dblp
%P 115-122
%T Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models.
%U http://dblp.uni-trier.de/db/conf/medes/medes2022.html#QadiTFR22
%@ 978-1-4503-9219-8
@inproceedings{conf/medes/QadiTFR22,
added-at = {2024-02-05T00:00:00.000+0100},
author = {Qadi, Ayoub El and Trocan, Maria and Frossard, Thomas and Rodríguez, Natalia Díaz},
biburl = {https://www.bibsonomy.org/bibtex/2d712aedd16e09a570b63a3f66dbbbdbf/dblp},
booktitle = {MEDES},
crossref = {conf/medes/2022},
editor = {Damiani, Ernesto and Silvestri, Claudio and Ivanovic, Mirjana and Chbeir, Richard and Manolopoulos, Yannis},
ee = {https://doi.org/10.1145/3508397.3564835},
interhash = {7e0315a36573fc00f01ae41a83f328f6},
intrahash = {d712aedd16e09a570b63a3f66dbbbdbf},
isbn = {978-1-4503-9219-8},
keywords = {dblp},
pages = {115-122},
publisher = {ACM},
timestamp = {2024-04-09T11:52:03.000+0200},
title = {Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models.},
url = {http://dblp.uni-trier.de/db/conf/medes/medes2022.html#QadiTFR22},
year = 2022
}