hi every body
I am using bootstrap sampling with neural network to select the best network architecture. For instance, if I use 30 bootstraping for each network, I would have 30 error for each training and test data related to them. To select the best model, should I use the variance of these errors and select the model with the lowest variance? and should the training and test error be considered separately for bootstrapping? Any other suggestion is welcomed.
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