Chapter 4. Classification
"It is a truth universally acknowledged, that a single man in possession of a good fortune, must be in want of a wife." | ||
| --Jane Austen, Pride and Prejudice | ||
In the previous chapter, we learned how to make numeric predictions using linear regression. The model we built was able to learn how the features of Olympic swimmers related to their weight and we were able to use the model to make a weight prediction for a new swimmer. As with all regression techniques, our output was a number.
Not all predictions demand a numeric solution, though—sometimes we want our predictions to be items. For example, we may want to predict which candidate a voter will back in an election. Or we may want to know which of several products a customer ...
Get Clojure for Data Science now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
