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
Research on Features of Learning Engagement Based on Random..:
, In:
2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)
,
Wang, Ping
;
Liu, Ke-man
- p. 1088-1093 , 2022
Link:
https://doi.org/10.1109/ICMSP55950.2022.9858950
RT T1
2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)
: T1
Research on Features of Learning Engagement Based on Random Forest
UL https://suche.suub.uni-bremen.de/peid=ieee-9858950&Exemplar=1&LAN=DE A1 Wang, Ping A1 Liu, Ke-man YR 2022 K1 Machine learning algorithms K1 Education K1 Semantics K1 Signal processing algorithms K1 Signal processing K1 Behavioral sciences K1 Classification algorithms K1 Learning Engagement K1 Random Forest K1 Feature importance SP 1088 OP 1093 LK http://dx.doi.org/https://doi.org/10.1109/ICMSP55950.2022.9858950 DO https://doi.org/10.1109/ICMSP55950.2022.9858950 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)