What is partition function in ML

In machine learning, the partition function is a normalization constant that is used in probabilistic models to ensure that the probabilities computed for each possible outcome sum up to 1. It is also known as the normalizing constant, the Z function, or the evidence. The partition function is calculated by summing up the probabilities of all possible outcomes of a model or distribution, and it is typically used in models such as the Boltzmann machine, the Ising model, and the maximum entropy model. The partition function is an important concept in statistical physics and is used to calculate the thermodynamic properties of physical systems.