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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study

To understand each cluster’s unique combination of variables separately, after the FPDC algorithm assigned participants to clusters, we applied a feature selection model (the statistically equivalent signature [SES] algorithm [42]) for cluster Cj with fixed j {1,…,k} based on binary logistic regression as a conditional independence test [32]. The cluster assignment is decoded in such a way that With this, a binary classification problem was thus created.

Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Maastricht Study Management, Iris M Kanera