November 2017
Beginner to intermediate
366 pages
7h 59m
English
Content preview from R Data Analysis Projects
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Model-based approach
The model based approach addresses the scalability problem seen in memory-based approaches. Compared to the user-based approach, where the recommendations came from leveraging a user's neighbors preference, the model-based approach leverages product similarity to make recommendations. The premise is that users will prefer those products similar to the ones they have already rated.
The first step in this approach is to calculate the product similarity matrix. Let us say there are a set of products: {p1,p2,...pm}. An m x m matrix is constructed to begin with. Once again Pearson coefficient or cosine similarity is used as a similarity measure. For efficiency purposes, instead of building a whole m x m matrix, a smaller ...
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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.