From the course: Building a Recommendation System with Python Machine Learning and AI

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Classification-based collaborative filtering

Classification-based collaborative filtering

From the course: Building a Recommendation System with Python Machine Learning and AI

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Classification-based collaborative filtering

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- [Presenter] Another useful form of collaborative filtering is classification based collaborative filtering. These recommenders could be powered by logistic regression or a Naive Bayes classifiers for example. For our demo, we're going to focus on using logistic regression model as a recommender. Just to refresh, logistic regression is a simple machine learning method you can use to predict the value of a numeric categorical variable based on its relationship with predictor variables. One of the awesome features of classification based recommenders is that they're able to make personalized recommendations. That's because these recommenders take into account user attributes as well as purchase history and other contextual data. So for example, when it comes to user attribute data, the dataset might define key characteristics of users that purchased or did not purchase in the past. And for purchase history, these data sets describe what purchases users have made or have not made in the…

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