Check all that apply:

Which of the following has the potential to discover both features and classes from experience:

Which of the following rules cannot be found using normal association rule mining?

Classification requires us to first assign labels to training data. What technique could one use to discover such labels in the first place?

Why do we prefer to insist that $X$ and $Y$ have non-negative entries?