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 Methods for Detecting Car Insurance Fraud:..:
, In:
2023 3rd International Conference on Intelligent Technologies (CONIT)
,
Singhal, Anisha
;
Singhal, Neha
;
Divya
. - p. 1-5 , 2023
Link:
https://doi.org/10.1109/CONIT59222.2023.10205670
RT T1 <cTitle>2023 3rd International Conference on Intelligent Technologies (CONIT)</cTitle>: T1 <Title>Machine Learning Methods for Detecting Car Insurance Fraud: Comparative Analysis</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10205670&Exemplar=1&LAN=DE A1 Singhal, Anisha A1 Singhal, Neha A1 Divya A1 Sharma, Kanchan YR 2023 K1 Support vector machines K1 Logistic regression K1 Machine learning algorithms K1 Insurance K1 Forestry K1 Prediction algorithms K1 Fraud K1 Automobile Insurance K1 Random Forest K1 Prediction K1 Data Analysis K1 Fraud Detection SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/CONIT59222.2023.10205670 DO https://doi.org/10.1109/CONIT59222.2023.10205670 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
