Here we aim to understand how exactly "Logistic Regression", a method that seems only to be used for classification problems, is indeed a regression algorithm.

We will as per the trend thus far, detail closed-form and approximate solutions to the loss function on this page. Furthermore, we will see how this type of regression is still a member of the GLM (generalised linear models) family, and we shall witness the derivation of the loss function by assuming our data is Bernoulli distributed.

Finally we shall see how predicting probabilities over a continuous range can be interpretted as classification.