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I am attempting to generate confidence intervals for a neural network, according to the article here, one would bootstrap from the training set to generate new models several times, and then apply the model to the validation set n number of times to generate the relevant statistics.

Is there another way to generate confidence intervals that doesn't require retraining the network? Retraining the network is very computationally intense and requires a great deal of time-- so I would like to avoid it if at all possible.

Thanks so much!

Edward Tyler
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  • are you looking specifically for confidence intervals, or would you be interested also in credible intervals? – DeltaIV Jan 23 '18 at 20:32
  • If credible intervals are an important consideration with neural nets then I would be interested in hearing about them as they pertain to this matter. – Edward Tyler Jan 23 '18 at 21:34
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    I think you will find the information you need in the linked threads. Please read them. If they aren't what you want / you still have a question afterwards, come back here & edit your question to state what you learned & what you still need to know. Then we can provide the information you need without just duplicating material elsewhere that already didn't help you. – gung - Reinstate Monica Jan 24 '18 at 13:20

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