Regression models map input data to an output prediction of a numerical value, as opposed to classification models that predict categorical labels. The distinction is most easily conveyed through examples:
- Regression models can predict output such as housing prices, long jump distances, or number of home runs hit
- Classification models can assign labels such as true/false, low/medium/high risk, or which animal species
I will use the prediction nomenclature described earlier in the chapter for the entire regression section. Make sure that you are familiar with the nomenclature before reading further.
