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J Csda 2011 09 008 by DEBORA POMPILIO LEITE is a document available to read on EtoBox.
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The document introduces a mixed effects least squares support vector machine (LS-SVM) model designed for classifying longitudinal data, addressing the challenges posed by unbalanced observations over time. This methodology combines regression modeling with classification, allowing for straightforward application to both binary and multi-class problems. The proposed model is validated through simulations and real-life applications, particularly in the context of human growth data.
- Author
- DEBORA POMPILIO LEITE
- Language
- EN