Results

eNauka >  Results >  Robustness of XGBoost Algorithm to Missing Features for Binary Classification of Medical Data
Title: Robustness of XGBoost Algorithm to Missing Features for Binary Classification of Medical Data
Authors: S. Stokanović ; D. Đukić; N. Miljković  
Issue Date: 2024
Publication: 2024 23rd International Symposium INFOTEH-JAHORINA (INFOTEH)
ISSN: 2767-9454 Search Idenfier
Publisher: IEEE
Type: Conference Paper
Collation: str. in-print
DOI: 10.1109/INFOTEH60418.2024.10495929
WoS-ID: 001215550500010
Scopus-ID: 2-s2.0-85192142724
URI: https://enauka.gov.rs/handle/123456789/906075
http://zaposleni.etf.bg.ac.rs/rest/sciNaucniRezultati/oai/record/3/709557
M-category: 
Mp. category will be shown later

6
SCOPUSTM
5
WEB OF SCIENCETM
Altmetric
Dimensions
Unpaywall

Google ScholarTM

Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.