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They suggested that an initial Bayesian model averaging (BMA) step could be used to provide a weighted set of models from which resamples could be based in a second bootstrap model selection step.
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In each of the five imputed data sets the two step bootstrap model selection procedure as described above was applied.
Our study showed that the application of this two-step bootstrap model selection procedure provides valuable information on model stability.
A two-step bootstrap model selection procedure [ 9, 11] was applied to provide information on model stability.
When fewer potential predictors are retained after the first step of the bootstrap model selection procedure, this variability seemed to decrease and model selection frequency increased.
Variable selection is a special case of a model selection step.
This heuristic avoids the model selection step and reduces the runtime of the preprocessing step.
In this model selection step, 3B makes many local decisions to incrementally adjust the model.
Furthermore, the bootstrap model selection routine gave additional information on model stability.
Yet the addition of a bootstrap model selection procedure showed that the MI-5 model might still be unstable.
Furthermore, the practical utility of the additional information provided by the bootstrap model selection procedure in prognostic modeling is demonstrated.
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