I am trying to establish 95% confidence intervals for metrics such as root mean square error, accuracy, precision etc for a neural network using the bootstrap method.
For 1,000 bootstraps, do I run the model 1,000 times and use those results, or do I bootstrap the model's results from one run through and use those results?