Archives for evaluation of recommender system
Recommender systems help individuals in excluding the overwhelming choices of our daily lives. However, while such systems learn patterns from historical data, they can capture the bias mediated by the underlying data about imbalances and inequality.
A recommender system, sometimes known as a recommendation engine, is a type of information filtering system that attempts to forecast a user's "rating" or "preference" for an item. In this post, we will look at RGRecSys, a library that performs constraint evaluation of recommender systems.