[D] CNN with Gaussian classifier instead of softmax • r/MachineLearning

A Gaussian classifier or nearest mean classifier just uses the mean of each class to make classifications. It therefore assumes classes are spherical Gaussians. The softmax on a CNN by contrast is more like multinomial logistic regression, which learns linear boundaries like a nearest mean classifier, but not the same boundary. I want to force the CNN to learn features in the last layer such that it has a prototype (mean) for each category, and uses a nearest mean rule to make classifications.