Predicting the Failure Risk of Internal Fixation Devices in Chinese Patients Undergoing Spinal Internal Fixation Surgery: Development and Assessment of a New Predictive Nomogram

Figure 2

Feature selection using the LASSO binary logistic regression model. (a) Feature selection by the LASSO binary logistic regression model. By verifying the optimal parameter (lambda) in the LASSO model, the partial likelihood deviance (binomial deviance) curve was plotted versus log (lambda). Dotted vertical lines were drawn based on 1 SE of the minimum criteria (the 1-SE criteria). (b) Feature selection by the LASSO binary logistic regression model. A coefficient profile plot was produced against the log (lambda) sequence in Figure 2(a). Four features with nonzero coefficients were selected by optimal lambda. LASSO: least absolute shrinkage and selection operator; SE: standard error.

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