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
Stacking Based LightGBM-CatBoost-RandomForest Algorithm and..:
, In:
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)
,
Wang, Zhihong
;
Ren, Hongru
;
Lu, Renquan
. - p. 1-6 , 2022
Link:
https://doi.org/10.1109/DOCS55193.2022.9967714
RT T1 <cTitle>2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)</cTitle>: T1 <Title>Stacking Based LightGBM-CatBoost-RandomForest Algorithm and Its Application in Big Data Modeling</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9967714&Exemplar=1&LAN=DE A1 Wang, Zhihong A1 Ren, Hongru A1 Lu, Renquan A1 Huang, Lirong YR 2022 K1 Stacking K1 Big Data K1 Predictive models K1 Prediction algorithms K1 Data models K1 Classification algorithms K1 Ensemble learning K1 Big Data Model K1 LightGBM-CatBoost-RandomForest SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/DOCS55193.2022.9967714 DO https://doi.org/10.1109/DOCS55193.2022.9967714 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
