The table below enumerates the models and the values of the method argument, as well as the complexity parameters used by train. The combination with the optimal resampling statistic is chosen as the final model and the entire training set is used to fit a final model.Ī variety of models are currently available. Across each data set, the performance of held-out samples is calculated and the mean and standard deviation is summarized for each combination. For particular model, a grid of parameters (if any) is created and the model is trained on slightly different data for each candidate combination of tuning parameters.
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