September 2015
Intermediate to advanced
158 pages
3h 9m
English
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Chapter 4. Evaluating the Recommender Systems
The previous chapter showed you how to build recommender systems. There are a few options, and some of them can be developed using the recommenderlab package. In addition, each technique has some parameters. After we build the models, how can we decide which one to use? How can we determine its parameters? We can first test the performance of some models and/or parameter configurations and then choose the one that performs best.
This chapter will show you how to evaluate recommender models, compare their performances, and choose the most appropriate model. In this chapter, we will cover the following topics:
- Preparing the data to evaluate performance
- Evaluating the performance of some models
- Choosing the ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.