if there is only a discrete number of possible outcomes (called categories), the process becomes a . . . . . . . .

The correct answer is B. Classification.

In classification, the goal is to predict the category of a given input. For example, we might want to classify images of cats and dogs, or classify emails as spam or not spam.

In regression, the goal is to predict a continuous value. For example, we might want to predict the price of a house, or the height of a person.

Modelfree is not a valid option.

Categories is a term that is used to describe the possible outcomes in a classification problem. For example, in the problem of classifying images of cats and dogs, the categories would be “cat” and “dog”.

I hope this helps!