Given a set of inputs/independent variables/predictors x and outputs/dependent variables/targets y, the goal is to learn a function f(x) that approximates y. This is accomplished by supervising f (x) that is, providing it with examples (x1, y1), …, (xn, yn). In other words, supervised learning involves providing labelled data to train the model on.
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