Chapter 2. Introducing recommenders
This chapter covers
- What recommenders are, within Mahout
- A first look at a recommender in action
- Evaluating the accuracy and quality of recommender engines
- Evaluating a recommender on a real data set: GroupLens
Each day we form opinions about things we like, don’t like, and don’t even care about. It happens unconsciously. You hear a song on the radio and either notice it because it’s catchy, or because it sounds awful—or maybe you don’t notice it at all. The same thing happens with T-shirts, salads, hairstyles, ski resorts, faces, and television shows.
Although people’s tastes vary, they do follow patterns. People tend to like things that are similar to other things they like. Because Sean loves bacon-lettuce-and-tomato ...
Get Mahout in Action 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.