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
Division of dataset into training and validation subsets by..:
, In:
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)
,
Yan, Shaomin
;
Wu, Guang
- p. 671-675 , 2022
Link:
https://doi.org/10.1109/AEMCSE55572.2022.00136
RT T1 <cTitle>2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)</cTitle>: T1 <Title>Division of dataset into training and validation subsets by the jackknife validations to predict the pH optimum for beta-cellobiosidase</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9948416&Exemplar=1&LAN=DE A1 Yan, Shaomin A1 Wu, Guang YR 2022 K1 Training K1 Industries K1 Computers K1 Biological system modeling K1 Computational modeling K1 Neurons K1 Predictive models K1 neural network K1 beta-cellobiosidase K1 jackknife validation K1 pH optimization K1 training sub-dataset K1 validation sub-dataset K1 prediction SP 671 OP 675 LK http://dx.doi.org/https://doi.org/10.1109/AEMCSE55572.2022.00136 DO https://doi.org/10.1109/AEMCSE55572.2022.00136 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
