Understanding large prediction intervals #510
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jesuinovieira
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In some cases, the prediction intervals produced can be very large or even infinite. Based on my experience, this issue often arises from insufficient data for calibration and fitting of the residual estimator – which may lead to a poorly fitted residual estimator, unrepresentative samples for calibration, or both.
Question
Given that there is sufficient data and the estimator is well-fitted to the training data, what other factors could cause unexpectedly large prediction intervals? For example, I guess that out-of-distribution data is one of the reasons. Are there other potential issues to be aware of that might indicate when the prediction intervals might not be reliable?
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