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Updated: Aug 9, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
A genetic algorithm-based, hybrid machine learning approach to model selection
Robert R Bies1, Matthew F Muldoon, Bruce G Pollock
1Department of Pharmaceutical Sciences and Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. rrb47@pitt.edu
Abstract:
We describe a general and robust method for identification of an optimal non-linear mixed effects model. This includes structural, inter-individual random effects, covariate effects and residual error models using machine learning. This method is based on combinatorial optimization using genetic algorithm.
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