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
Comparison Performance of C4.5, Naïve Bayes and K-Nearest N..:
, In:
2019 5th International Conference on Science in Information Technology (ICSITech)
,
Islamiyah
;
Afiyah, Anisa Nur
;
Dengen, Nataniel
. - p. 112-117 , 2019
Link:
https://doi.org/10.1109/ICSITech46713.2019.8987455
RT T1
2019 5th International Conference on Science in Information Technology (ICSITech)
: T1
Comparison Performance of C4.5, Naïve Bayes and K-Nearest Neighbor in Determination Drug Rehabilitation
UL https://suche.suub.uni-bremen.de/peid=ieee-8987455&Exemplar=1&LAN=DE A1 Islamiyah A1 Afiyah, Anisa Nur A1 Dengen, Nataniel A1 Taruk, Medi YR 2019 K1 Performance Algorithm K1 C4.5 K1 Naïve Bayes K1 K-Nearest Neighbors K1 Drug Rehabilitation SP 112 OP 117 LK http://dx.doi.org/https://doi.org/10.1109/ICSITech46713.2019.8987455 DO https://doi.org/10.1109/ICSITech46713.2019.8987455 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)