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
Using Multiple AI Classification Models to Predict the Winn..:
, In:
2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
,
Laurel, Kristian Elijah Y.
;
Gutierrez, Arielle Neena R.
;
Tan, Kean Anderson S.
. - p. 693-694 , 2023
Link:
https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226891
RT T1
2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)
: T1
Using Multiple AI Classification Models to Predict the Winner of a League of Legends (LoL) Game Based on its First 10-Minutes of Gameplay
UL https://suche.suub.uni-bremen.de/peid=ieee-10226891&Exemplar=1&LAN=DE A1 Laurel, Kristian Elijah Y. A1 Gutierrez, Arielle Neena R. A1 Tan, Kean Anderson S. A1 Baldovino, Renann G. YR 2023 SN 2575-8284 K1 Support vector machines K1 Training K1 Games K1 Machine learning K1 Diamonds K1 Predictive models K1 Consumer electronics K1 classification K1 MOBA K1 sklearn K1 tensorflow SP 693 OP 694 LK http://dx.doi.org/https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226891 DO https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226891 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)