gression

.hi-slate[Supervised learning] is broken into two types, based on what kind of .hi-orange[output] we want to predict:

1. .hi-slate[Classification tasks] for which the values of `\(\color{#FFA500}{\mathbf{y}}\)` are discrete categories.
&lt;br&gt;*E.g.*, race, sex, loan default, hazard, disease, flight status

2. .hi-slate[Regression tasks] in which `\(\color{#FFA500}{\mathbf{y}}\)` takes on continuous, numeric values.
&lt;br&gt;*E.g.*, price, arrival time, number of emails, temperature

.note[Not