A comparison of penalised regression methods for informing the selection of predictive markers.
Christopher J GreenwoodGeorge J YoussefPrimrose LetcherJacqui A MacdonaldLauryn J HaggAnn SansonJenn McintoshDelyse M HutchinsonJohn W ToumbourouMatthew Fuller-TyszkiewiczCraig A OlssonPublished in: PloS one (2020)
Although overall predictive accuracy was only marginally better with penalised logistic regression methods, benefits were most clear in their capacity to select a manageable subset of indicators. Preference to competing penalised logistic regression methods may therefore be guided by feature selection capability, and thus interpretative considerations, rather than predictive performance alone.
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