We use Logistic Regression (LR) to solve binary or 2-class classification problems. LR produces a single value between 0 to 1.

The depth of decision tree represents the degree of how optimal it is. We first need to know that the longest tree leads to a model that learns more complex information i.e. overfitting. On the other hand, shallower trees prone to learn less complex information i.e. underfitting.