Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration

DOI10.1111/BIOM.12343zbMath1419.62323OpenAlexW1490796347WikidataQ30980714 ScholiaQ30980714MaRDI QIDQ2809516

Donglin Zeng, Yuanjia Wang, Tianle Chen

Publication date: 30 May 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4713389

zbMATH Keywords

statistical learningintegrative analysisdisease predictionlatent effects

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05)

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Cites Work

• Unnamed Item
• A mixed effects least squares support vector machine model for classification of longitudinal data
• Explicit connections between longitudinal data analysis and kernel machines
• Functional Linear Discriminant Analysis for Irregularly Sampled Curves
• A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines

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