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
Cardiovascular Disease Forecast using Machine Learning Para..:
, In:
2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)
,
Islam, Saiful
;
Jahan, Nusrat
;
Khatun, Mst. Eshita
- p. 487-490 , 2020
Link:
https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00091
RT T1
2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)
: T1
Cardiovascular Disease Forecast using Machine Learning Paradigms
UL https://suche.suub.uni-bremen.de/peid=ieee-9076424&Exemplar=1&LAN=DE A1 Islam, Saiful A1 Jahan, Nusrat A1 Khatun, Mst. Eshita YR 2020 K1 Classification Algorithm K1 Heart Diseases K1 Decision Tree K1 SVM K1 Logistic Regression K1 Naive Bayes K1 UCI dataset SP 487 OP 490 LK http://dx.doi.org/https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00091 DO https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00091 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)