Maximum entropy

Maximum entropy is a principle used to make the most unbiased prediction or estimate based on known information. It involves choosing the probability distribution that fits the known data but assumes the least beyond that, avoiding unwarranted assumptions. Think of it as selecting the most "spread out" or "uncertain" distribution that still aligns with what you know, ensuring no unjustified biases influence the outcome. This approach helps in fields like data analysis, machine learning, and physics to create models that are as objective and balanced as possible given the available information.