Multivariate binary classification of imbalanced datasets—A case study based on high‐dimensional multiplex autoimmune assay data

DOI10.1002/bimj.201600207zbMath1391.62245OpenAlexW2700200406WikidataQ36408725 ScholiaQ36408725MaRDI QIDQ5364037

Laura Schlieker, Angelika Lueking, Katja Ickstadt, Peter Schulz-Knappe, Carmen Theek, Anna Telaar

Publication date: 2 October 2017

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201600207

zbMATH Keywords

sampling random forests imbalanced data cost-sensitive learning high-dimensional multiplex autoimmune assay data multivariate binary classification PPLS-DA

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

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