Tag: convex optimisation

• Logistic Regression: Deriving the Sigmoid and the Cross Entropy from Maximum LikelihoodThe sigmoid and the logit turn a linear score into a probability, and Bernoulli maximum likelihood turns into the cross entropy error; the gradient and Hessian show the loss is convex but has no closed form.Computer ScienceMathematics for Machine LearningUndergraduatelogistic regressionsigmoid functioncross entropymaximum likelihoodconvex optimisation~28 min