Overview
The maximum entropy principle is a idea used to derive a distribution over events from a set of measurements. Rather than finding the maximum likelihood distribution, it returns the maximum uncertainty (entropy) distribution consistent with the observations.
The justification for this principle is that an analyst should choose a distribution consistent with available data, but without assuming anything about the information not available.