That is, we model the logarithm of the probability of seeing a given output using the linear predictor as well as an additional normalization factor, the logarithm of the partition function:
In essence, we estimate the logarithm of the likelihood of seeing a particular output using not only the linear predictor but also an additional element that accounts for the total number of possible outcomes.