I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Machine Learning For Detecting Credit Card Fraud:
, In:
2022 IEEE North Karnataka Subsection Flagship International Conference (NKCon)
,
Gupta, Aanchal
;
Singh, Kanishka
;
Sharma, Nonita
. - p. 1-6 , 2022
Link:
https://doi.org/10.1109/NKCon56289.2022.10126861
RT T1 <cTitle>2022 IEEE North Karnataka Subsection Flagship International Conference (NKCon)</cTitle>: T1 <Title>Machine Learning For Detecting Credit Card Fraud</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10126861&Exemplar=1&LAN=DE A1 Gupta, Aanchal A1 Singh, Kanishka A1 Sharma, Nonita A1 Rakhra, Manik YR 2022 K1 Training K1 Machine learning algorithms K1 Forestry K1 Credit cards K1 Fraud K1 Classification algorithms K1 Decision trees K1 Credit Card Frauds K1 Training system through Decision Tree Classifiers K1 Random Forest Algorithms K1 machine learning models SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/NKCon56289.2022.10126861 DO https://doi.org/10.1109/NKCon56289.2022.10126861 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
