  Understanding prediction errors and determining how to fix them is critical
to building effective predictive systems. In this paper, we delineate four
types of prediction errors and demonstrate that these four types characterize
all prediction errors. In addition, we describe potential remedies and tools
that can be used to reduce the uncertainty when trying to determine the source
of a prediction error and when trying to take action to remove a prediction
errors.
