How to build nomogram for type 2 diabetes using a naïve Bayesian classifier technique

DOI10.1080/02664763.2018.1450366OpenAlexW2791611029MaRDI QIDQ5036543

Jea-Young Lee, Jae-Cheol Park

Publication date: 23 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2018.1450366

zbMATH Keywords

incidence ratenaïve Bayesian classifiernomogramrisk factor (attribute)type 2 diabetes (T2D)

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items (2)

Nomogram construction to predict dyslipidemia based on a logistic regression analysis ⋮ How to construct a nomogram for hypertension using complex sampling data from Korean adults

Cites Work

• Logit Models from Economics and Other Fields
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