As you have already seen, the loss to be predicted contains continuous values, that is, it will be a regression task. So in using regression analysis here, the goal is to predict a continuous target variable, whereas another area called classification predicts a label from a finite set.
Logistic regression (LR) belongs to the family of regression algorithms. The goal of regression is to find relationships and dependencies between variables. It models the relationship between a continuous scalar dependent variable y (that is, label or target) and one or more (a D-dimensional vector) explanatory variable (also independent variables, input variables, features, observed data, observations, attributes, ...
