on age and gender then age and gender are features and the height you want to find is the label and if you have a training set with a lot of people with their height corresponding to age and gender then you have a labeled training set so the first category is called supervised learning and in supervised learning you have training data that consists of a set of training examples you have a labeled training set and the basic idea is to find the most optimal model parameters to predict unknown labels on other objects let's look at a few examples